Developmental roadmap for antimicrobial susceptibility testing systems

Quantitative drug susceptibility testing for Mycobacterium tuberculosis using unassembled sequencing data and machine learning

There remains a clinical need for better approaches to rapid drug susceptibility testing in view of the increasing burden of multidrug resistant tuberculosis. Binary susceptibility phenotypes only capture changes in minimum inhibitory concentration when these cross the critical concentration, even though other changes may be clinically relevant. We developed a machine learning system to predict minimum inhibitory concentration from unassembled whole-genome sequencing data for 13 anti-tuberculosis drugs. We trained, validated and tested the system on 10,859 isolates from the CRyPTIC dataset. Essential agreement rates (predicted MIC within one doubling dilution of observed MIC) were above 92% for first-line drugs, 91% for fluoroquinolones and aminoglycosides, and 90% for new and repurposed drugs, albeit with a significant drop in performance for the very few phenotypically resistant isolates in the latter group. To further validate the model in the absence of external MIC datasets, we predicted MIC and converted values to binary for an external set of 15,239 isolates with binary phenotypes, and compare their performance against a previously validated mutation catalogue, the expected performance of existing molecular assays, and World Health Organization Target Product Profiles. The sensitivity of the model on the external dataset was greater than 90% for all drugs except ethionamide, clofazimine and linezolid. Specificity was greater than 95% for all drugs except ethambutol, ethionamide, bedaquiline, delamanid and clofazimine. The proposed system can provide quantitative susceptibility phenotyping to help guide antimicrobial therapy, although further data collection and validation are required before machine learning can be used clinically for all drugs.

Fluorometric determination of mecA gene in MRSA with a graphene-oxide based bioassay using flap endonuclease 1-assisted target recycling and Klenow fragment-triggered signal amplification

Methicillin-resistant Staphylococcus aureus (MRSA) is a multidrug-resistant bacterium that causes a wide range of illnesses, necessitating the development of new technologies for its detection. Herein, we propose a graphene oxide (GO)-based sensing platform for the detection of mecA gene in MRSA using flap endonuclease 1 (FEN1)-assisted target recycling and Klenow fragment (KF)-triggered signal amplification. Without the target, all the DNA probes were adsorbed onto GO, resulting in fluorescence quenching of the dye. Upon the addition of the target, a triple complex was formed that triggered FEN1-assisted target recycling and initiated two polymerization reactions with the assistance of KF polymerase, generating numerous dsDNA that were repelled by GO. These dsDNAs triggered fluorescence enhancement when SYBR Green I was added. Therefore, the target DNA was quantified by measuring the fluorescence at excitation and emission wavelengths of 480/526 nm. This mecA gene assay showed a good linear range from 1 to 50 nM with a lower limit of detection of 0.26 nM, and displayed good applicability to the analysis of real samples. Thus, a new method for monitoring MRSA has been developed that has great potential for early clinical diagnosis and treatment.

Rapid and Simple Morphological Assay for Determination of Susceptibility/Resistance to Combined Ciprofloxacin and Ampicillin, Independently, in Escherichia coli

Current antibiograms cannot discern the particular effect of a specific antibiotic when the bacteria are incubated with a mixture of antibiotics. To prove that this task is achievable, Escherichia coli strains were treated with ciprofloxacin for 45 min, immobilized on a slide and stained with SYBR Gold. In susceptible strains, the nucleoid relative surface started to decrease near the MIC, being progressively condensed as the dose increased. The shrinkage level correlated with the DNA fragmentation degree. Ciprofloxacin-resistant bacilli showed no change. Additionally, E. coli strains were incubated with ampicillin for 45 min and processed similarly. The ampicillin-susceptible strain revealed intercellular DNA fragments that increased with dose, unlike the resistant strain. Co-incubation with both antibiotics revealed that ampicillin did not modify the nucleoid condensation effect of ciprofloxacin, whereas the quinolone partially decreased the background of DNA fragments induced by ampicillin. Sixty clinical isolates, with different combinations of susceptibility-resistance to each antibiotic, were co-incubated with the EUCAST breakpoints of susceptibility of ciprofloxacin and ampicillin. The morphological assay correctly categorized all the strains for each antibiotic in 60 min, demonstrating the feasible independent evaluation of a mixture of quinolone and beta-lactam. The rapid phenotypic assay may shorten the incubation times and necessary microbial mass currently required for evaluation.

Development of Rapid Disk Diffusion Device Using Laser Speckle Formation Technology for Rapid Antimicrobial Susceptibility Testing

The escalation of antimicrobial resistance (AMR) due to the excessive and inappropriate use of antimicrobials has prompted the urgent need for more rapid and effective antimicrobial susceptibility testing (AST) methods. Conventional AST techniques often take 16-24 h, leading to empirical prescription practices and the potential emergence of AMR. The study aimed to develop a rapid disk diffusion (RDD) method utilizing laser speckle formation (LSF) technology to expedite AST results. The study aimed to evaluate the performance of LSF technology in determining antimicrobial susceptibility. In this study, preclinical and clinical settings were established to compare the LSF technology with conventional disk diffusion (DD) methods to measure the inhibition zones. Preclinical experiments with different bacterial strains demonstrated more than 70% categorical agreement (CA) against most antimicrobials. Further, clinical experiments with multiple strains and antibiotics revealed CA ranging from 40 to 79%, while major and minor discrepancies were observed around 30% and 11%, respectively. These observations revealed high concordance between RDD and DD for multiple antimicrobials in multiple species. The results underscore the potential of RDD-based LSF technology for hastening AST procedures. The current study is marked by a unique equipment setup and analysis approach. Collectively, the suggested laser-based RDD showed greater potential than previously developed comparable methods. The proposed method and design have a higher application potential than formerly developed similar technologies. Together, the study contributes to the ongoing development of rapid AST methods.

Rapid Phenotypic Antibiotics Susceptibility Analysis by a 3D Printed Prototype

One of the most important public health concerns is the increase in antibiotic-resistant pathogens and corresponding treatment of associated infections. Addressing this challenge requires more efficient use of antibiotics, achievable by the use of evidence-based, effective antibiotics identified by antibiotic susceptibility testing (AST). However, the current standard method of phenotypic AST used for this purpose requires 48 h or more from sample collection to result. Until results are available, broad-spectrum antibiotics are used to avoid delaying treatment. The turnaround time must therefore be shortened in order for the results to be available before the second administration of antibiotics. The phenotypic electrochemical AST method presented here identifies effective antibiotics within 5-10 h after sampling. Spiked serum samples, including polymicrobial samples, with clinically relevant pathogens and respective concentrations commonly found in bloodstream infections (Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, and Pseudomonas aeruginosa) are used. Direct loading of the test with diluted serum eliminates the need for a pre-culture, as required by existing methods. Furthermore, by combining several electrochemical measurement procedures with computational analysis, allowing the method to be used both online and offline, the AST achieves a sensitivity of 94.44% and a specificity of 95.83% considering each replicate individually.

Predicting S. aureus antimicrobial resistance with interpretable genomic space maps

Increasing antimicrobial resistance (AMR) represents a global healthcare threat. To decrease the spread of AMR and associated mortality, methods for rapid selection of optimal antibiotic treatment are urgently needed. Machine learning (ML) models based on genomic data to predict resistant phenotypes can serve as a fast screening tool prior to phenotypic testing. Nonetheless, many existing ML methods lack interpretability. Therefore, we present a methodology for visualization of sequence space and AMR prediction based on the non-linear dimensionality reduction method - generative topographic mapping (GTM). This approach, applied to AMR data of >5000 S. aureus isolates retrieved from the PATRIC database, yielded GTM models with reasonable accuracy for all drugs (balanced accuracy values ≥0.75). The Generative Topographic Maps (GTMs) represent data in the form of illustrative maps of the genomic space and allow for antibiotic-wise comparison of resistant phenotypes. The maps were also found to be useful for the analysis of genetic determinants responsible for drug resistance. Overall, the GTM-based methodology is a useful tool for both the illustrative exploration of the genomic sequence space and AMR prediction.

A capillary-based centrifugal indicator equipped with in situ pathogenic bacteria culture for fast antimicrobial susceptibility testing

Antimicrobial resistance has become a major global health threat due to the misuse and overuse of antibiotics. Rapid, affordable, and high-efficiency antimicrobial susceptibility testing (AST) is among the effective means to solve this problem. Herein, we developed a capillary-based centrifugal indicator (CBCI) equipped with an in situ culture of pathogenic bacteria for fast AST. The bacterial incubation and growth were performed by macro-incubation, which seamlessly integrated the capillary indicator. Through simple centrifugation, all the bacterial cells were confined at the nanoliter-level capillary column. The packed capillary column height could linearly reflect the bacterial count, and the minimum inhibitory concentration (MIC) was determined based on the difference in the column height between the drug-added groups and the control group. The AST results could easily be determined by the naked eye or smartphone imaging. Thus, the CBCI realized the combination of macro-bacterial incubation and early micro assessment, which accelerated the phenotypic AST without complex microscopic counting or fluorescent labelling. The whole operation process was simple and easy to use. AST results could be determined for E. coli ATCC strains within 3.5 h, and the output results for clinical samples were consistent with the hospital reports. We expect this AST platform to become a useful tool in limiting antimicrobial resistance, especially in remote/resource-limited areas or in underdeveloped countries.

In-depth analysis of the treatment effect and synergistic mechanism of TanReQing injection on clinical multi-drug resistant Pseudomonas aeruginosa

Antibiotic resistance is a recognized and concerning public health issue. Gram-negative bacilli, such as Pseudomonas aeruginosa (P. aeruginosa), are notorious for their rapid development of drug resistance, leading to treatment failures. TanReQing injection (TRQ) was chosen to explore its pharmacological mechanisms against clinical multidrug-resistant P. aeruginosa (MDR-PA), given its antibacterial and anti-inflammatory properties. We revealed the expression of proteins and genes in P. aeruginosa after co-culture with TRQ. This study developed an assessment method to evaluate clinical resistance of P. aeruginosa using MALDI-TOF MS identification and Biotyper database searching techniques. Additionally, it combined MIC determination to investigate changes in MDR-PA treated by TRQ. TRQ effectively reduced the MICs of ceftazidime and cefoperazone and enhanced the confidence scores of MDR-PA as identified by mass spectrometry. Using this evaluation method, the fingerprints of standard P. aeruginosa and MDR-PA were compared, and the characteristic peptide sequence (Seq-PA No. 1) associated with flagellum was found. The phenotypic experiments were conducted to confirm the effect of TRQ on the motility and adhesion of P. aeruginosa. A combination of co-immunoprecipitation and proteome analysis was employed, and 16 proteins were significantly differentially expressed and identified as potential candidates for investigating the mechanism of inhibiting resistance in P. aeruginosa treated by TRQ. The candidates were verified by quantitative real-time PCR analysis, and TRQ may affect these core proteins (MexA, MexB, OprM, OprF, OTCase, IDH, and ASL) that influence resistance of P. aeruginosa. The combination of multiple methods helps elucidate the synergistic mechanism of TRQ in overcoming resistance of P. aeruginosa.IMPORTANCEPseudomonas aeruginosa is an opportunistic pathogen closely associated with various life-threatening acute and chronic infections. The presence of antimicrobial resistance and multidrug resistance in P. aeruginosa infections significantly complicates antibiotic treatment. The expression of β-lactamase, efflux systems such as MexAB-OprM, and outer membrane permeability are considered to have the greatest impact on the sensitivity of P. aeruginosa. The study used a method to assess the clinical resistance of P. aeruginosa using matrix-assisted laser desorption ionization time of flight mass spectrometry identification and Biotyper database search techniques. TanReQing injection (TRQ) effectively reduced the MICs of ceftazidime and cefoperazone in multidrug-resistant P. aeruginosa (MDR-PA) and improved the confidence scores for co-cultured MDR-PA. The study found a characteristic peptide sequence for distinguishing whether P. aeruginosa is resistant. Through co-immunoprecipitation and proteome analysis, we explored the mechanism of TRQ overcoming resistance of P. aeruginosa.

Microfluidic systems for infectious disease diagnostics

Microorganisms, encompassing both uni- and multicellular entities, exhibit remarkable diversity as omnipresent life forms in nature. They play a pivotal role by supplying essential components for sustaining biological processes across diverse ecosystems, including higher host organisms. The complex interactions within the human gut microbiota are crucial for metabolic functions, immune responses, and biochemical signalling, particularly through the gut-brain axis. Viruses also play important roles in biological processes, for example by increasing genetic diversity through horizontal gene transfer when replicating inside living cells. On the other hand, infection of the human body by microbiological agents may lead to severe physiological disorders and diseases. Infectious diseases pose a significant burden on global healthcare systems, characterized by substantial variations in the epidemiological landscape. Fast spreading antibiotic resistance or uncontrolled outbreaks of communicable diseases are major challenges at present. Furthermore, delivering field-proven point-of-care diagnostic tools to the most severely affected populations in low-resource settings is particularly important and challenging. New paradigms and technological approaches enabling rapid and informed disease management need to be implemented. In this respect, infectious disease diagnostics taking advantage of microfluidic systems combined with integrated biosensor-based pathogen detection offers a host of innovative and promising solutions. In this review, we aim to outline recent activities and progress in the development of microfluidic diagnostic tools. Our literature research mainly covers the last 5 years. We will follow a classification scheme based on the human body systems primarily involved at the clinical level or on specific pathogen transmission modes. Important diseases, such as tuberculosis and malaria, will be addressed more extensively.

Antimicrobial Agent Functional Gold Nanocluster-Mediated Multichannel Sensor Array for Bacteria Sensing

Urinary tract infections (UTIs) have greatly affected human health in recent years. Accurate and rapid diagnosis of UTIs can enable a more effective treatment. Herein, we developed a multichannel sensor array for efficient identification of bacteria based on three antimicrobial agents (vancomycin, lysozyme, and bacitracin) functional gold nanoclusters (AuNCs). In this sensor, the fluorescence intensity of the three AuNCs was quenched to varying degrees by the bacterial species, providing a unique fingerprint for different bacteria. With this sensing platform, seven pathogenic bacteria, different concentrations of the same bacteria, and even bacterial mixtures were successfully differentiated. Furthermore, UTIs can be accurately identified with our sensors in ∼30 min with 100% classification accuracy. The proposed sensing systems offer a rapid, high-throughput, and reliable sensing platform for the diagnosis of UTIs.

Sentinel laboratory compliance with best practices in Burkina Faso's antimicrobial resistance surveillance network

Background

Standardising procedures is the best way to harmonise and strengthen the quality of laboratory-based antimicrobial resistance surveillance. Since 2018, Burkina Faso has developed and disseminated the national manual of procedures for performing antibiotic susceptibility tests in sentinel laboratories within its national antimicrobial resistance surveillance network.

Objective

Our study aimed to assess these sentinel laboratories' compliance with good practices for antibiotics susceptibility tests.

Methods

Four teams evaluated the antimicrobial resistance sentinel sites laboratories throughout Burkina Faso from 19 to 28 September 2022. Eighteen out of 19 sentinel laboratories were evaluated. A four-member technical committee designed and validated the evaluation tool composed of three Microsoft Excel sheets. The evaluation emphasised quality controls for culture media, antibiotic discs and compliance with antimicrobial susceptibility testing procedures by the laboratories. Excel software was used for data recording and graphs and table design. The free R software version 4.2.0 was used for descriptive statistics. An overall score below 80% was considered noncompliance.

Results

Most (83.33%) of the sentinel laboratories conducted at least one quality control activity for culture media, and 66.67% conducted at least one quality control activity for antibiotic discs. Over three-quarters (76.47%) of the laboratories were more than 80% compliant with the modified Kirby Bauer antimicrobial susceptibility testing method.

Conclusion

The evaluation revealed the noncompliance of sentinel laboratories with the national procedure manual, particularly in the quality control component.

What this study adds

This study has provided baseline data on the sentinel laboratories' compliance with the national antimicrobial susceptibility testing procedures manual, particularly in areas performing quality control checks or meeting quality indicators for culture media and antibiotic discs.

Metabolism-Triggered Plasmonic Nanosensor for Bacterial Detection and Antimicrobial Susceptibility Testing of Clinical Isolates

Antimicrobial resistance (AMR) is predicted to become the leading cause of death worldwide in the coming decades. Rapid and on-site antibiotic susceptibility testing (AST) is crucial for guiding appropriate antibiotic choices to combat AMR. With this in mind, we have designed a simple and efficient plasmonic nanosensor consisting of Cu2+ and cysteine-modified AuNP (Au/Cys) that utilizes the metabolic activity of bacteria toward Cu2+ for bacterial detection and AST. When Cu2+ is present, it induces the aggregation of Au/Cys. However, in the presence of bacteria, Cu2+ is metabolized to varying extents, resulting in distinct levels of aggregation. Moreover, the metabolic activity of bacteria can be influenced by their antibiotic susceptibility, allowing us to differentiate between susceptible and resistant strains through direct color changes from the Cu2+-Au/Cys platform over approximately 3 h. These color changes can be easily detected using naked-eye observation, smartphone analysis, or absorption readout. We have validated the platform using four clinical isolates and six types of antibiotics, demonstrating a clinical sensitivity and specificity of 95.8%. Given its simplicity, low cost, high speed, and high accuracy, the plasmonic nanosensor holds great potential for point-of-care detection of antibiotic susceptibility across various settings.

Antimicrobial resistance in multistate outbreaks of nontyphoidal Salmonella infections linked to animal contact-United States, 2015-2018

Animal contact is an established risk factor for nontyphoidal Salmonella infections and outbreaks. During 2015-2018, the U.S. Centers for Disease Control and Prevention (CDC) and other U.S. public health laboratories began implementing whole-genome sequencing (WGS) of Salmonella isolates. WGS was used to supplement the traditional methods of pulsed-field gel electrophoresis for isolate subtyping, outbreak detection, and antimicrobial susceptibility testing (AST) for the detection of resistance. We characterized the epidemiology and antimicrobial resistance (AMR) of multistate salmonellosis outbreaks linked to animal contact during this time period. An isolate was considered resistant if AST yielded a resistant (or intermediate, for ciprofloxacin) interpretation to any antimicrobial tested by the CDC or if WGS showed a resistance determinant in its genome for one of these agents. We identified 31 outbreaks linked to contact with poultry (n = 23), reptiles (n = 6), dairy calves (n = 1), and guinea pigs (n = 1). Of the 26 outbreaks with resistance data available, we identified antimicrobial resistance in at least one isolate from 20 outbreaks (77%). Of 1,309 isolates with resistance information, 247 (19%) were resistant to ≥1 antimicrobial, and 134 (10%) were multidrug-resistant to antimicrobials from ≥3 antimicrobial classes. The use of resistance data predicted from WGS increased the number of isolates with resistance information available fivefold compared with AST, and 28 of 43 total resistance patterns were identified exclusively by WGS; concordance was high (>99%) for resistance determined by AST and WGS. The use of predicted resistance from WGS enhanced the characterization of the resistance profiles of outbreaks linked to animal contact by providing resistance information for more isolates.

Antimicrobial susceptibility testing using infrared attenuated total reflection (IR-ATR) spectroscopy to monitor metabolic activity

Fast and accurate detection of antimicrobial resistance in pathogens remains a challenge, and with the increase in antimicrobial resistance due to mis- and overuse of antibiotics, it has become an urgent public health problem. We demonstrate how infrared attenuated total reflection (IR-ATR) can be used as a simple method for assessment of bacterial susceptibility to antibiotics. This is achieved by monitoring the metabolic activities of bacterial cells via nutrient consumption and using this as an indicator of bacterial viability. Principal component analysis of the obtained spectra provides a tool for fast and simple discrimination of antimicrobial resistance in the acquired data. We demonstrate this concept using four bacterial strains and four different antibiotics, showing that the change in glucose concentration in the growth medium after 2 h, as monitored by IR-ATR, can be used as a spectroscopic diagnostic technique, to reduce detection time and to improve quality in the assessment of antimicrobial resistance in pathogens.

Advances, limitations, and considerations on the use of vibrational spectroscopy towards the development of management decision tools in food safety

Food safety and food security are two of the main concerns for the modern food manufacturing industry. Disruptions in the food supply and value chains have created the need to develop agile screening tools that will allow the detection of food pathogens, spoilage microorganisms, microbial contaminants, toxins, herbicides, and pesticides in agricultural commodities, natural products, and food ingredients. Most of the current routine analytical methods used to detect and identify microorganisms, herbicides, and pesticides in food ingredients and products are based on the use of reliable and robust immunological, microbiological, and biochemical techniques (e.g. antigen-antibody interactions, extraction and analysis of DNA) and chemical methods (e.g. chromatography). However, the food manufacturing industries are demanding agile and affordable analytical methods. The objective of this review is to highlight the advantages and limitations of the use of vibrational spectroscopy combined with chemometrics as proxy to evaluate and quantify herbicides, pesticides, and toxins in foods.

Rapid Drug Susceptibility Testing to Preserve Antibiotics

Antibiotic resistance is a global challenge likely to cost trillions of dollars in excess costs in the health system and more importantly, millions of lives every year. A major driver of resistance is the absence of susceptibility testing at the time a healthcare worker needs to prescribe an antimicrobial. The effect is that many prescriptions are unintentionally wasted and expose mutable organisms to antibiotics increasing the risk of resistance emerging. Often simplistic solutions are applied to this growing issue, such as a naïve drive to increase the speed of drug susceptibility testing. This puts a spotlight on a technological solution and there is a multiplicity of such candidate DST tests in development. Yet, if we do not define the necessary information and the speed at which it needs to be available in the clinical decision-making progress as well as the necessary integration into clinical pathways, then little progress will be made. In this chapter, we place the technological challenge in a clinical and systems context. Further, we will review the landscape of some promising technologies that are emerging and attempt to place them in the clinic where they will have to succeed.

Expert guidance on target product profile development for AMR diagnostic tests

Diagnostics are widely considered crucial in the fight against antimicrobial resistance (AMR), which is expected to kill 10 million people annually by 2030. Nevertheless, there remains a substantial gap between the need for AMR diagnostics versus their development and implementation. To help address this problem, target product profiles (TPP) have been developed to focus developers' attention on the key aspects of AMR diagnostic tests. However, during discussion between a multisectoral working group of 51 international experts from industry, academia and healthcare, it was noted that specific AMR-related TPPs could be extended by incorporating the interdependencies between the key characteristics associated with the development of such TPPs. Subsequently, the working group identified 46 characteristics associated with six main categories (ie, Intended Use, Diagnostic Question, Test Description, Assay Protocol, Performance and Commercial). The interdependencies of these characteristics were then identified and mapped against each other to generate new insights for use by stakeholders. Specifically, it may not be possible for diagnostics developers to achieve all of the recommendations in every category of a TPP and this publication indicates how prioritising specific TPP characteristics during diagnostics development may influence (or not) a range of other TPP characteristics associated with the diagnostic. The use of such guidance, in conjunction with specific TPPs, could lead to more efficient AMR diagnostics development.

Application of diagnostic network optimization in Kenya and Nepal to design integrated, sustainable and efficient bacteriology and antimicrobial resistance surveillance networks

Antimicrobial resistance (AMR) is a major global public health concern, particularly in low- and middle-income countries, which experience the highest burden of AMR. Critical to combatting AMR is ensuring there are effective, accessible diagnostic networks in place to diagnose, monitor and prevent AMR, but many low- and middle-income countries lack such networks. Consequently, there is substantial need for approaches that can inform the design of efficient AMR laboratory networks and sample referral systems in lower-resource countries. Diagnostic network optimization (DNO) is a geospatial network analytics approach to plan diagnostic networks and ensure greatest access to and coverage of services, while maximizing the overall efficiency of the system. In this intervention, DNO was applied to strengthen bacteriology and AMR surveillance network design in Kenya and Nepal for human and animal health, by informing linkages between health facilities and bacteriology testing services and sample referral routes between farms, health facilities and laboratories. Data collected from the target settings in each country were entered into the open-access DNO tool OptiDx, to generate baseline scenarios, which depicted the current state of AMR laboratory networks and sample referral systems in the countries. Subsequently, baselines were adjusted to evaluate changing factors such as samples flows, transport frequency, transport costs, and service distances. Country stakeholders then compared resulting future scenarios to identify the most feasible solution for their context. The DNO analyses enabled a wealth of insights that will facilitate strengthening of AMR laboratory and surveillance networks in both countries. Overall, the project highlights the benefits of using a data-driven approach for designing efficient diagnostic networks, to ensure better health resource allocation while maximizing the impact and equity of health interventions. Given the critical need to strengthen AMR laboratory and surveillance capacity, DNO should be considered an integral part of diagnostic strategic planning in the future.

Multiplex Real-Time PCR for the Detection of Tetracycline, Ciprofloxacin, and Erythromycin Resistance Determinants from Human and Foodborne Campylobacter jejuni and Campylobacter coli

Campylobacter jejuni and Campylobacter coli are the predominant thermophilic species responsible for foodborne gastroenteritis worldwide. Elevated resistance to certain antibiotics was observed due to antimicrobial therapy in farm animals and humans, while reduced antimicrobial usage partially reduced antibiotic resistance. Monitoring the antimicrobial resistance demonstrated a substantial fraction of multi-resistant isolates, indicating the necessity of reliable tools for their detection. In this study, resistance determinants in 129 German and 21 Vietnamese isolates were selected to establish a novel multiplex real-time PCR (qPCR), facilitating the simultaneous detection of four resistance determinants. These comprised tet(O) gene variants associated with tetracycline resistance, point mutations GyrA_T86I and GyrA_T86V associated with ciprofloxacin resistance, and the erm(B) gene together with the point mutation A2075G in the 23S rRNA gene, associated with erythromycin resistance. Moreover, the performance of the qPCR assay was evaluated by comparing the results of qPCR to phenotypic antimicrobial resistance profiles, obtained with standardized EUCAMP3 microdilution panel, which showed 100% similarity (inclusivity and exclusivity). Variation in measurement methods, including qPCR machines and master mixes showed robustness, essential for laboratories. The assay can be used for the rapid detection of resistance determinants, and is beneficial for monitoring the spread of antibiotic resistance in C. jejuni and C. coli.

Augmented surveillance of antimicrobial resistance with high-throughput robotics detects transnational flow of fluoroquinolone-resistant Escherichia coli strain into poultry

BACKGROUND

Food animal AMR surveillance programs assess only small numbers of Escherichia coli (from 100 to 600 per animal class) nationally each year, severely limiting the evaluation of public health risk(s). Here we demonstrate an affordable approach for early detection of emerging resistance on a broad scale that can also accurately characterize spatial and temporal changes in resistance.

METHODS

Caecal samples (n = 295) obtained from 10 meat poultry were screened using high-throughput robotics. Initial screening via agar dilution (5310 plates) quantified AMR carriage (cfu/g) for each sample. Ciprofloxacin-resistant isolates (n = 91) proceeded to downstream broth microdilution susceptibility testing. A subset of 28 ciprofloxacin-resistant isolates underwent WGS and phylogenetic analysis.

RESULTS

Intra- and inter-flock carriage of resistance varied with drug class. Ampicillin and tetracycline resistance was ubiquitous to most birds in all flocks with an average carriage rate of 5.8 log10 cfu/g. Gentamicin and ciprofloxacin-resistant E. coli colonized fewer birds, and had an average carriage rate of 1.2 log10 cfu/g and 1.0 log10 cfu/g of faeces, respectively. Resistance to extended-spectrum cephalosporins was absent. ST354 was the dominant ST among the WGS isolates, but they demonstrated markedly lower resistance gene carriage than their international counterparts.

CONCLUSIONS

These data amply demonstrate the ineffectiveness of commonly relied-on approaches to AMR surveillance for achieving early detection of emergence, or for measuring spatial and temporal resistance trends. Genetic analysis suggested there has been transnational flow of a ciprofloxacin-resistant strain into Australian poultry flocks, explaining their detection in a nation that prohibits fluoroquinolone use in poultry.

Dissolvable alginate hydrogel-based biofilm microreactors for antibiotic susceptibility assays

Biofilms are found in many infections in the forms of surface-adhering aggregates on medical devices, small clumps in tissues, or even in synovial fluid. Although antibiotic resistance genes are studied and monitored in the clinic, the structural and phenotypic changes that take place in biofilms can also lead to significant changes in how bacteria respond to antibiotics. Therefore, it is important to better understand the relationship between biofilm phenotypes and resistance and develop approaches that are compatible with clinical testing. Current methods for studying antimicrobial susceptibility are mostly planktonic or planar biofilm reactors. In this work, we develop a new type of biofilm reactor-three-dimensional (3D) microreactors-to recreate biofilms in a microenvironment that better mimics those in vivo where bacteria tend to form surface-independent biofilms in living tissues. The microreactors are formed on microplates, treated with antibiotics of 1000 times of the corresponding minimal inhibitory concentrations (1000 × MIC), and monitored spectroscopically with a microplate reader in a high-throughput manner. The hydrogels are dissolvable on demand without the need for manual scraping, thus enabling measurements of phenotypic changes. Bacteria inside the biofilm microreactors are found to survive exposure to 1000 × MIC of antibiotics, and subsequent comparison with plating results reveals no antibiotic resistance-associated phenotypes. The presented microreactor offers an attractive platform to study the tolerance and antibiotic resistance of surface-independent biofilms such as those found in tissues.

WHY STOP? A prospective observational vignette-based study to determine the cognitive-behavioural effects of rapid diagnostic PCR-based point-of-care test results on antibiotic cessation in ICU infections

OBJECTIVES

Point-of-care tests (POCTs) for infection offer accurate rapid diagnostics but do not consistently improve antibiotic stewardship (ASP) of suspected ventilator-associated pneumonia. We aimed to measure the effect of a negative PCR-POCT result on intensive care unit (ICU) clinicians' antibiotic decisions and the additional effects of patient trajectory and cognitive-behavioural factors (clinician intuition, dis/interest in POCT, risk averseness).

DESIGN

Observational cohort simulation study.

SETTING

ICU.

PARTICIPANTS

70 ICU consultants/trainees working in UK-based teaching hospitals.

METHODS

Clinicians saw four case vignettes describing patients who had completed a course of antibiotics for respiratory infection. Vignettes comprised clinical and biological data (ie, white cell count, C reactive protein), varied to create four trajectories: clinico-biological improvement (the 'improvement' case), clinico-biological worsening ('worsening'), clinical improvement/biological worsening ('discordant clin better'), clinical worsening/biological improvement ('discordant clin worse'). Based on this, clinicians made an initial antibiotics decision (stop/continue) and rated confidence (6-point Likert scale). A PCR-based POCT was then offered, which clinicians could accept or decline. All clinicians (including those who declined) were shown the result, which was negative. Clinicians updated their antibiotics decision and confidence.

MEASURES

Antibiotics decisions and confidence were compared pre-POCT versus post-POCT, per vignette.

RESULTS

A negative POCT result increased the proportion of stop decisions (54% pre-POCT vs 70% post-POCT, χ2(1)=25.82, p<0.001, w=0.32) in all vignettes except improvement (already high), most notably in discordant clin worse (49% pre-POCT vs 74% post-POCT). In a linear regression, factors that significantly reduced clinicians' inclination to stop antibiotics were a worsening trajectory (b=-0.73 (-1.33, -0.14), p=0.015), initial confidence in continuing (b=0.66 (0.56, 0.76), p<0.001) and involuntary receipt of POCT results (clinicians who accepted the POCT were more inclined to stop than clinicians who declined it, b=1.30 (0.58, 2.02), p<0.001). Clinician risk averseness was not found to influence antibiotic decisions (b=-0.01 (-0.12, 0.10), p=0.872).

CONCLUSIONS

A negative PCR-POCT result can encourage antibiotic cessation in ICU, notably in cases of clinical worsening (where the inclination might otherwise be to continue). This effect may be reduced by high clinician confidence to continue and/or disinterest in POCT, perhaps due to low trust/perceived utility. Such cognitive-behavioural and trajectorial factors warrant greater consideration in future ASP study design.

Microwell-enhanced optical rapid antibiotic susceptibility testing of single bacteria

Bacteria that are resistant to antibiotics present an increasing burden on healthcare. To address this emerging crisis, novel rapid antibiotic susceptibility testing (AST) methods are eagerly needed. Here, we present an optical AST technique that can determine the bacterial viability within 1 h down to a resolution of single bacteria. The method is based on measuring intensity fluctuations of a reflected laser focused on a bacterium in reflective microwells. Using numerical simulations, we show that both refraction and absorption of light by the bacterium contribute to the observed signal. By administering antibiotics that kill the bacteria, we show that the variance of the detected fluctuations vanishes within 1 h, indicating the potential of this technique for rapid sensing of bacterial antibiotic susceptibility. We envisage the use of this method for massively parallelizable AST tests and fast detection of drug-resistant pathogens.

Portable Colorimetric Hydrogel Beads for Point-of-Care Antimicrobial Susceptibility Testing

Sepsis is a life-threatening condition with systemic inflammatory responses caused by bacterial infections. Considering the emergence of antibiotic-resistant bacteria such as methicillin-resistant Staphylococcus aureus (MRSA), sepsis is a great threat to public health. The gold standard methods for antimicrobial susceptibility testing (AST), however, take at least approximately 3 days to implement the entire blood culture, pure culture, and AST processes. To overcome the time-consuming nature of conventional AST, a method employing a chromatic biosensor composed of poly(diacetylene), alginate, and LB broth (PAL) is introduced in this study. Compared to the gold standards, AST with PAL biosensors can be completed within a time frame as short as 16 h. Such a significant reduction in time is possible because the consecutive cultures and AST are carried out simultaneously by encapsulating the bacterial nutrients and detection molecules into a single component. The bead-like hydrogel sensors were used in their freeze-dried form, which endows them with portability and stability, thus making them adequate for point-of-care testing. The PAL biosensor yields minimum inhibitory concentrations comparable to those from the Clinical and Laboratory Standards Institute, and the applicability of the biosensor is further shown in MRSA-infected mice.

High-throughput functional trait testing for bacterial pathogens

Functional traits are characteristics that affect the fitness and metabolic function of a microorganism. There is growing interest in using high-throughput methods to characterize bacterial pathogens based on functional virulence traits. Traditional methods that phenotype a single organism for a single virulence trait can be time consuming and labor intensive. Alternatively, machine learning of whole-genome sequences (WGS) has shown some success in predicting virulence. However, relying solely on WGS can miss functional traits, particularly for organisms lacking classical virulence factors. We propose that high-throughput assays for functional virulence trait identification should become a prominent method of characterizing bacterial pathogens on a population scale. This work is critical as we move from compiling lists of bacterial species associated with disease to pathogen-agnostic approaches capable of detecting novel microbes. We discuss six key areas of functional trait testing and how advancing high-throughput methods could provide a greater understanding of pathogens.

Current and Future Technologies for the Detection of Antibiotic-Resistant Bacteria

Antibiotic resistance is a global public health concern, posing a significant threat to the effectiveness of antibiotics in treating bacterial infections. The accurate and timely detection of antibiotic-resistant bacteria is crucial for implementing appropriate treatment strategies and preventing the spread of resistant strains. This manuscript provides an overview of the current and emerging technologies used for the detection of antibiotic-resistant bacteria. We discuss traditional culture-based methods, molecular techniques, and innovative approaches, highlighting their advantages, limitations, and potential future applications. By understanding the strengths and limitations of these technologies, researchers and healthcare professionals can make informed decisions in combating antibiotic resistance and improving patient outcomes.

Simple and Rapid Discrimination of Methicillin-Resistant Staphylococcus aureus Based on Gram Staining and Machine Vision

Methicillin-resistant Staphylococcus aureus (MRSA) is a clinical threat with high morbidity and mortality. Here, we describe a new simple, rapid identification method for MRSA using oxacillin sodium salt, a cell wall synthesis inhibitor, combined with Gram staining and machine vision (MV) analysis. Gram staining classifies bacteria as positive (purple) or negative (pink) according to the cell wall structure and chemical composition. In the presence of oxacillin, the integrity of the cell wall for methicillin-susceptible S. aureus (MSSA) was destroyed immediately and appeared Gram negative. In contrast, MRSA was relatively stable and appeared Gram positive. This color change can be detected by MV. The feasibility of this method was demonstrated in 150 images of the staining results for 50 clinical S. aureus strains. Based on effective feature extraction and machine learning, the accuracies of the linear linear discriminant analysis (LDA) model and nonlinear artificial neural network (ANN) model for MRSA identification were 96.7% and 97.3%, respectively. Combined with MV analysis, this simple strategy improved the detection efficiency and significantly shortened the time needed to detect antibiotic resistance. The whole process can be completed within 1 h. Unlike the traditional antibiotic susceptibility test, overnight incubation is avoided. This new strategy could be used for other bacteria and represents a new rapid method for detection of clinical antibiotic resistance. IMPORTANCE Oxacillin sodium salt destroys the integrity of the cell wall of MSSA immediately, appearing Gram negative, whereas MRSA is relatively stable and still appears Gram positive. This color change can be detected by microscopic examination and MV analysis. This new strategy has significantly reduced the time to detect resistance. The results show that using oxacillin sodium salt combined with Gram staining and MV analysis is a new, simple and rapid method for identification of MRSA.

Risk Factors for the In-Hospital Mortality in Pyogenic Vertebral Osteomyelitis: A Cross-Sectional Study on 9753 Patients

BACKGROUND

Pyogenic vertebral osteomyelitis represents a clinical challenge associated with significant morbidity and mortality. The aim of this study was to analyze potential risk factors for the in-hospital mortality of vertebral osteomyelitis (VO) patients.

METHODS

Based on the International Classification of Diseases, 10th Revision (ICD-10) codes for VO ("M46.2-", "M46.3-", and "M46.4-") data for total case numbers, secondary diagnoses, and numbers of in-hospital deaths were extracted from the Institute for the Hospital Remuneration System (InEK GmbH). Odds ratios (OR) for death were calculated for several secondary diseases and factors of interest.

RESULTS

Despite age, certain comorbidities were found to be strongly associated with increased mortality risk: Heart failure (OR = 2.80; 95% CI 2.45 to 3.20; p < 0.01), chronic kidney disease (OR = 1.83; 95% CI 1.57 to 2.13; p < 0.01), and diabetes with complications (OR = 1.86; 95% CI 1.46 to 2.38; p < 0.01). Among the complications, acute liver failure showed the highest risk for in-hospital mortality (OR = 42.41; 95% CI 23.47 to 76.62; p < 0.01). Additionally, stage III kidney failure (OR = 9.81; 95% CI 7.96 to 12.08; p < 0.01), sepsis (OR = 5.94; 95% CI 5.02 to 7.03; p < 0.01), acute respiratory failure (OR = 5.31; 95% CI 4.61 to 6.12; p < 0.01), and systemic inflammatory response syndrome (SIRS) (OR = 5.19; 95% CI 3.69 to 5.19; p < 0.01) were associated with in-hospital mortality. When analyzing the influence of pathogens, documented infection with Pseudomonas aeruginosa had the highest risk for mortality (OR = 2.74; 95% CI 2.07 to 3.63; p < 0.01), followed by Streptococci, Escherichia coli, and Staphylococcus aureus infections.

CONCLUSIONS

An early assessment of individual patient risk factors may be beneficial in the care and treatment of VO to help reduce the risks of mortality. These findings emphasize the importance of closely monitoring VO patients with chronic organ diseases, early detection and treatment of sepsis, and tailored empirical antibiotic therapy. The identification of specific pathogens and antibiotic susceptibility testing should be prioritized to improve patient outcomes in this high-risk population.

Contemporary Considerations for Establishing Reference Methods for Antibacterial Susceptibility Testing

Antibacterial susceptibility testing (AST) is performed to guide therapy, perform resistance surveillance studies, and support development of new antibacterial agents. For 5 decades, broth microdilution (BMD) has served as the reference method to assess in vitro activity of antibacterial agents against which both novel agents and diagnostic tests have been measured. BMD relies on in vitro inhibition or killing of bacteria. It is associated with several limitations: it is a poor mimic of the in vivo milieu of bacterial infections, requires multiple days to perform, and is associated with subtle, difficult to control variability. In addition, new reference methods will soon be needed for novel agents whose activity cannot be evaluated by BMD (e.g., those that target virulence). Any new reference methods must be standardized, correlated with clinical efficacy and be recognized internationally by researchers, industry, and regulators. Herein, we describe current reference methods for in vitro assessment of antibacterial activity and highlight key considerations for the generation of novel reference methods.

Application of machine learning in the prevention of periprosthetic joint infection following total knee arthroplasty: a systematic review

BACKGROUND

Machine learning is a promising and powerful technology with increasing use in orthopedics. Periprosthetic joint infection following total knee arthroplasty results in increased morbidity and mortality. This systematic review investigated the use of machine learning in preventing periprosthetic joint infection.

METHODS

A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. PubMed was searched in November 2022. All studies that investigated the clinical applications of machine learning in the prevention of periprosthetic joint infection following total knee arthroplasty were included. Non-English studies, studies with no full text available, studies focusing on non-clinical applications of machine learning, reviews and meta-analyses were excluded. For each included study, its characteristics, machine learning applications, algorithms, statistical performances, strengths and limitations were summarized. Limitations of the current machine learning applications and the studies, including their 'black box' nature, overfitting, the requirement of a large dataset, the lack of external validation, and their retrospective nature were identified.

RESULTS

Eleven studies were included in the final analysis. Machine learning applications in the prevention of periprosthetic joint infection were divided into four categories: prediction, diagnosis, antibiotic application and prognosis.

CONCLUSION

Machine learning may be a favorable alternative to manual methods in the prevention of periprosthetic joint infection following total knee arthroplasty. It aids in preoperative health optimization, preoperative surgical planning, the early diagnosis of infection, the early application of suitable antibiotics, and the prediction of clinical outcomes. Future research is warranted to resolve the current limitations and bring machine learning into clinical settings.

Addressing Consumer Misconceptions on Antibiotic Use and Resistance in the Context of Sore Throat: Learnings from Social Media Listening

A misunderstanding of the mechanism of action and bacterial targets of antibiotics by consumers may drive inappropriate antibiotic use and antimicrobial resistance (AMR). Tackling AMR requires an in-depth understanding of consumer beliefs and misconceptions. We explored consumer conversations on a number of social media platforms on antibiotic use and AMR in the context of sore throat and how coronavirus disease 2019 (COVID-19) affected online conversations between 1 January 2018 and 25 November 2021 across eight countries. Five distinct consumer groups were identified (antibiotic-preserving peer educators, antibiotic-cautious consumers, medication-resistant antibiotic opponents, believers in the strength of antibiotics, determined pro-antibiotic consumers) with a wide spectrum of beliefs around antibiotics in sore throat. Many opinions were based upon misconceptions, the most prominent of which was that antibiotics are strong medications that can treat all types of sore throat. COVID-19 had a multifaceted effect on the sore throat and AMR conversation. Sore throat triggered anxiety as consumers feared it may be a COVID-19 symptom while engagement in conversations around antibiotics for COVID-19 increased. Finally, consumers sought multiple routes to access antibiotics, such as directly from the pharmacy or by attempting to persuade physicians to prescribe. Knowledge obtained from this study could be used to develop focused approaches to dispel consumer misconceptions and mitigate AMR.

Rapid Phenotypic Antimicrobial Susceptibility Testing Using a Coulter Counter and Proliferation Rate Discrepancy

The rapid determination of antimicrobial susceptibility and evidence-based antimicrobial prescription is necessary to combat widespread antimicrobial resistance and promote effectively treatment for bacterial infections. This study developed a rapid phenotypic antimicrobial susceptibility determination method competent for seamless clinical implementation. A laboratory-friendly Coulter counter-based antimicrobial susceptibility testing (CAST) was developed and integrated with bacterial incubation, population growth monitoring, and result analysis to quantitatively detect differences in bacterial growth between resistant and susceptible strains following a 2 h exposure to antimicrobial agents. The distinct proliferation rates of the different strains enabled the rapid determination of their antimicrobial susceptibility phenotypes. We evaluated the performance efficacy of CAST for 74 clinically isolated Enterobacteriaceae subjected to 15 antimicrobials. The results were consistent with those obtained via the 24 h broth microdilution method, showing 90.18% absolute categorical agreement.

Regulation of probe density on upconversion nanoparticles enabling high-performance lateral flow assays

Upconversion nanoparticles (UCNPs)-based fluorescence probes have shown great potential in point-of-care testing (POCT) applications, due to UCNPs' features of high photostability and background-free fluorescence. Ceaseless improvements of UCNPs-probes have been carried out to increase detection sensitivity and to broaden detection range of UCNPs-based POCT. In this paper, we optimized UCNPs-probes by regulating probe density. The optimization was verified by a traditional lateral flow assay (LFA) platform for C-reactive protein (CRP) detection. Further, the optimized UCNPs-LFA integrating with a home-made benchtop fluorescence analyzer holds the capability to achieve high-performance POCT. Finally, nearly a 20 times sensitivity enhancement with a limit of detection of 0.046 ng/mL and a broad detection range of 0.2-300 ng/mL for CRP detection was obtained. Moreover, the optimized UCNPs-LFA was applied to detecting CRP in clinical serum samples and the detection results were consistent with the clinical test, validating its clinical practicability. The proposed optimization method is also expected to optimize other nanoparticles-based bio-probes for wider POCT application.

Next-generation nanophotonic-enabled biosensors for intelligent diagnosis of SARS-CoV-2 variants

Constantly mutating SARS-CoV-2 is a global concern resulting in COVID-19 infectious waves from time to time in different regions, challenging present-day diagnostics and therapeutics. Early-stage point-of-care diagnostic (POC) biosensors are a crucial vector for the timely management of morbidity and mortalities caused due to COVID-19. The state-of-the-art SARS-CoV-2 biosensors depend upon developing a single platform for its diverse variants/biomarkers, enabling precise detection and monitoring. Nanophotonic-enabled biosensors have emerged as 'one platform' to diagnose COVID-19, addressing the concern of constant viral mutation. This review assesses the evolution of current and future variants of the SARS-CoV-2 and critically summarizes the current state of biosensor approaches for detecting SARS-CoV-2 variants/biomarkers employing nanophotonic-enabled diagnostics. It discusses the integration of modern-age technologies, including artificial intelligence, machine learning and 5G communication with nanophotonic biosensors for intelligent COVID-19 monitoring and management. It also highlights the challenges and potential opportunities for developing intelligent biosensors for diagnosing future SARS-CoV-2 variants. This review will guide future research and development on nano-enabled intelligent photonic-biosensor strategies for early-stage diagnosing of highly infectious diseases to prevent repeated outbreaks and save associated human mortalities.

Analytical methods for assessing antimicrobial activity of nanomaterials in complex media: advances, challenges, and perspectives

Assessing the antimicrobial activity of engineered nanomaterials (ENMs), especially in realistic scenarios, is of great significance for both basic research and applications. Multiple analytical methods are available for analysis via off-line or on-line measurements. Real-world samples are often complex with inorganic and organic components, which complicates the measurements of microbial viability and/or metabolic activity. This article highlights the recent advances achieved in analytical methods including typical applications and specifics regarding their accuracy, cost, efficiency, and user-friendliness. Methodological drawbacks, technique gaps, and future perspectives are also discussed. This review aims to help researchers select suitable methods for gaining insight into antimicrobial activities of targeted ENMs in artificial and natural complex matrices.

Study of Laser Light Scattering Methods in Rapid Viability Assessment of Microorganisms under Antibiotics Exposure for Adaptation in Lab-on-A-Chip Format

The antibiotic resistance (ABR) problem is becoming increasingly disturbing and it is important to implement express methods of ABR testing to allow operative antibiotic therapy decisions. The application of laser light scattering (LLS) in microbiological analysis for express ABR testing of microorganisms has been considered. The ways of miniaturization of laser light scattering for creating the bases of their integration into microbiological laboratory-on-a-chip (MLOC) for clinical express diagnostics have been analysed. The advantage of miniaturization in the context of clinical express analysis realization problems are investigated. A system of parallel measuring cells and illumination, enabling simultaneous testing of a group of antibiotics, was tested by splitting a laser beam with a two-dimensional collimator prepared of nanoporous anodic aluminum oxide. It has been demonstrated that the application of LLS methods, providing high concentration and mass sensitivity as well as a miniaturization potential, is an effective approach in the development of new generation diagnostic instruments. The studies have demonstrated the ability of methods to register effects of antibiotics on microbiological samples within 10 min. The following microorganisms were used in the study: Escherichia coli M-17, Lactobacillus plantarum, Bifidobacterium bifidum, Stenotrophomonas maltophilia.

Antibiotic Resistance Diagnosis in ESKAPE Pathogens-A Review on Proteomic Perspective

Antibiotic resistance has emerged as an imminent pandemic. Rapid diagnostic assays distinguish bacterial infections from other diseases and aid antimicrobial stewardship, therapy optimization, and epidemiological surveillance. Traditional methods typically have longer turn-around times for definitive results. On the other hand, proteomic studies have progressed constantly and improved both in qualitative and quantitative analysis. With a wide range of data sets made available in the public domain, the ability to interpret the data has considerably reduced the error rates. This review gives an insight on state-of-the-art proteomic techniques in diagnosing antibiotic resistance in ESKAPE pathogens with a future outlook for evading the "imminent pandemic".

QMAC-dRAST for the direct testing of antibiotic susceptibility for Enterobacterales in positive blood-culture broth: a comparison of the performances with the MicroScan system and direct disc diffusion testing methods

OBJECTIVES

To evaluate the performances of the QMAC-dRAST GN (Gram-negative) kit for rapid antimicrobial sensitivity testing (AST) and two other methods, directly on positive blood-culture broth (PBCB), by comparison with a reference method: the MicroScan method based on broth microdilution on colonies isolated on PBCB subculture.

METHODS

In total, 156 samples were collected prospectively from blood cultures positive for a Gram-negative rod. Each sample was tested with four AST techniques: (i) the QMAC dRAST GN kit, (ii) the disc diffusion (DD) method, (iii) the MicroScan method applied directly to PBCB; and (iv) MicroScan with isolates from PBCB subculture, as a reference.

RESULTS

For 124 PBCB containing Enterobacterales, overall essential agreement (EA) and categorical agreement (CA) between the QMAC-dRAST on PBCB and the reference reached 95.7% and 93.5%, respectively. There were 3.0% very major errors (VME), 4.0% major errors (ME) and 2.8% minor errors (mE). A comparison of MicroScan on PBCB and the reference yielded 98.8% EA, 98.5% CA, and rates of 0.6% VME, 0.9% ME and 0.7% mE. The DD method on PBCB gave a CA of 95.8% and rates of 1.7% for VME, 2.0% for ME and 1.9% for mE. Results were obtained more rapidly for QMAC-dRAST (median of 6 h 37 min versus 18 h for the MicroScan and DD methods on PBCB).

CONCLUSIONS

The QMAC-dRAST system provided rapid results well correlated with the reference method on PBCB containing Enterobacterales. Given the shorter time-to-results, the QMAC-dRAST system constitutes a fast and reliable alternative to conventional AST methods.

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.

A sprayed graphene transistor platform for rapid and low-cost chemical sensing

We demonstrate a novel and versatile sensing platform, based on electrolyte-gated graphene field-effect transistors, for easy, low-cost and scalable production of chemical sensor test strips. The Lab-on-PCB platform is enabled by low-boiling, low-surface-tension sprayable graphene ink deposited on a substrate manufactured using a commercial printed circuit board process. We demonstrate the versatility of the platform by sensing pH and Na⁺ concentrations in an aqueous solution, achieving a sensitivity of 143 ± 4 μA per pH and 131 ± 5 μA per log₁₀Na⁺, respectively, in line with state-of-the-art graphene chemical sensing performance.

Optical photothermal infrared spectroscopy: A novel solution for rapid identification of antimicrobial resistance at the single-cell level via deuterium isotope labeling

The rise and extensive spread of antimicrobial resistance (AMR) has become a growing concern, and a threat to the environment and human health globally. The majority of current AMR identification methods used in clinical setting are based on traditional microbiology culture-dependent techniques which are time-consuming or expensive to be implemented, thus appropriate antibiotic stewardship is provided retrospectively which means the first line of treatment is to hope that a broad-spectrum antibiotic works. Hence, culture-independent and single-cell technologies are needed to allow for rapid detection and identification of antimicrobial-resistant bacteria and to support a more targeted and effective antibiotic therapy preventing further development and spread of AMR. In this study, for the first time, a non-destructive phenotyping method of optical photothermal infrared (O-PTIR) spectroscopy, coupled with deuterium isotope probing (DIP) and multivariate statistical analysis was employed as a metabolic fingerprinting approach to detect AMR in Uropathogenic Escherichia coli (UPEC) at both single-cell and population levels. Principal component-discriminant function analysis (PC-DFA) of FT-IR and O-PTIR spectral data showed clear clustering patterns as a result of distinctive spectral shifts (C-D signature peaks) originating from deuterium incorporation into bacterial cells, allowing for rapid detection and classification of sensitive and resistant isolates at the single-cell level. Furthermore, the single-frequency images obtained using the C-D signature peak at 2,163 cm^-1 clearly displayed the reduced ability of the trimethoprim-sensitive strain for incorporating deuterium when exposed to this antibiotic, compared to the untreated condition. Hence, the results of this study indicated that O-PTIR can be employed as an efficient tool for the rapid detection of AMR at the single-cell level.

Nanotechnology Involved in Treating Urinary Tract Infections: An Overview

Considered as the most frequent contaminations that do not require hospitalization, urinary tract infections (UTIs) are largely known to cause significant personal burdens on patients. Although UTIs overall are highly preventable health issues, the recourse to antibiotics as drug treatments for these infections is a worryingly spread approach that should be addressed and gradually overcome in a contemporary, modernized healthcare system. With a virtually alarming global rise of antibiotic resistance overall, nanotechnologies may prove to be the much-needed 'lifebuoy' that will eventually suppress this prejudicial phenomenon. This review aims to present the most promising, currently known nano-solutions, with glimpses on clinical and epidemiological aspects of the UTIs, prospective diagnostic instruments, and non-antibiotic treatments, all of these engulfed in a comprehensive overview.

Management of Bacterial and Fungal Infections in the ICU: Diagnosis, Treatment, and Prevention Recommendations

Bacterial and fungal infections are common issues for patients in the intensive care unit (ICU). Large, multinational point prevalence surveys have identified that up to 50% of ICU patients have a diagnosis of bacterial or fungal infection at any one time. Infection in the ICU is associated with its own challenges. Causative organisms often harbour intrinsic and acquired mechanisms of drug-resistance, making empiric and targeted antimicrobial selection challenging. Infection in the ICU is associated with worse clinical outcomes for patients. We review the epidemiology of bacterial and fungal infection in the ICU. We discuss risk factors for acquisition, approaches to diagnosis and management, and common strategies for the prevention of infection.

Unmet needs for management of drug-resistant infections: low- and middle-income countries' viewpoint

Drug-resistant infections are a serious threat globally which demands cost-effective solutions to meet the unmet needs in their diagnosis and treatment. Gram-negative pathogens, drug-resistant tuberculosis, and multidrug-resistant Salmonella typhi have been reported as cause of resistant infections in developing countries. Here, we discuss the priority pathogens and conditions for which feasible solutions adaptable to low-resource settings are required to address the antimicrobial resistance in pathogens. These solutions will be helpful in containing the spread of antimicrobial resistance and better patient outcomes.

Overcoming Antibiotic Resistance with Novel Paradigms of Antibiotic Selection

Conventional antimicrobial susceptibility tests, including phenotypic and genotypic methods, are insufficiently accurate and frequently fail to identify effective antibiotics. These methods predominantly select therapies based on the antibiotic response of only the lead bacterial pathogen within pure bacterial culture. However, this neglects the fact that, in the majority of human infections, the lead bacterial pathogens are present as a part of multispecies communities that modulate the response of these lead pathogens to antibiotics and that multiple pathogens can contribute to the infection simultaneously. This discrepancy is a major cause of the failure of antimicrobial susceptibility tests to detect antibiotics that are effective in vivo. This review article provides a comprehensive overview of the factors that are missed by conventional antimicrobial susceptibility tests and it explains how accounting for these methods can aid the development of novel diagnostic approaches.

Recent Developments in Electrochemical Sensors for the Detection of Antibiotic-Resistant Bacteria

The development of efficient point-of-care (POC) diagnostic tools for detecting infectious diseases caused by destructive pathogens plays an important role in clinical and environmental monitoring. Nevertheless, evolving complex and inconsistent antibiotic-resistant species mire their drug efficacy. In this regard, substantial effort has been expended to develop electrochemical sensors, which have gained significant interest for advancing POC testing with rapid and accurate detection of resistant bacteria at a low cost compared to conventional phenotype methods. This review concentrates on the recent developments in electrochemical sensing techniques that have been applied to assess the diverse latent antibiotic resistances of pathogenic bacteria. It deliberates the prominence of biorecognition probes and tailor-made nanomaterials used in electrochemical antibiotic susceptibility testing (AST). In addition, the bimodal functional efficacy of nanomaterials that can serve as potential transducer electrodes and the antimicrobial agent was investigated to meet the current requirements in designing sensor module development. In the final section, we discuss the challenges with contemporary AST sensor techniques and extend the key ideas to meet the demands of the next POC electrochemical sensors and antibiotic design modules in the healthcare sector.

Advances in the screening of antimicrobial compounds using electrochemical biosensors: is there room for nanomaterials?

The abusive use of antimicrobial compounds and the associated appearance of antimicrobial resistant strains are a major threat to human health. An improved antimicrobial administration involves a faster diagnosis and detection of resistances. Antimicrobial susceptibility testing (AST) are the reference techniques for this purpose, relying mainly in the use of culture techniques. The long time required for analysis and the lack of reproducibility of these techniques have fostered the development of high-throughput AST methods, including electrochemical biosensors. In this review, recent electrochemical methods used in AST have been revised, with particular attention on those used for the evaluation of new drug candidates. The role of nanomaterials in these biosensing platforms has also been questioned, inferring that it is of minor importance compared to other applications.

The landscape of bacterial antibiotic susceptibility in a multi-tier ophthalmology network in India: an electronic medical record driven analytics report

Introduction. Injudicious use of antibiotics often leads to antibiotic resistance which contributes to significant morbidity and mortality. Knowledge of local antibiogram is important in informing appropriate empiric antimicrobial therapy.

Hypothesis / Gap. It is the first and largest study that examines bacterial isolates from multiple ocular infections across South India and provides a overview of susceptibility patterns for each individual bacteria in the detailed interactive dashboard.

Aim. To study the landscape of bacterial antibiotic susceptibility patterns of ocular infections in patients undergoing microbiological investigations across a multi-tier ophthalmology network in India.

Methodology. This cross-sectional hospital-based study included 15 822 patients in whom microbiology samples were analysed between September 2013 and December 2021. Ocular tissue of patients in whom a microbiology sample was processed in at least one eye were included as cases. The data were collected using an indigenously developed electronic medical record (EMR) system.

Results. Among the 15 822 patients, bacteria (51.06 %) was the most common aetiology, followed by fungus (38.27 %). The majority of the patients were male (68.10 %) and the majority were adults (90.01 %). The most common age group was during the sixth decade with 2914 (18.42 %) patients. The patients were more commonly from the lower socio-economic status (51.61 %) and rural geography (46.82 %). The majority of the specimens sent for microbiological analysis were corneal scraping (68.61 %). Gram-positive cocci and Gram-positive bacilli were most sensitive towards vancomycin (86.83 and 92.89% respectively) followed by cefazolin (80.88 %) and amikacin, while Gram-negative bacilli were most sensitive towards ofloxacin (65.24%).

Conclusion. The most common aetiology of infection in ocular disease is bacterial and the majority of the patients presented from the rural geography and from lower socio-economic status. While vancomycin continues to be the drug of choice for Gram-positive organisms, increasing resistance to fluoroquinolones and ceftazidime was observed. Adoption of this model will enable access to antimicrobial susceptibility data, leading to reliable decisions and better clinical outcomes.

Fluorescent metabolic labeling-based quick antibiotic susceptibility test for anaerobic bacteria

Because of the advancements in medicine and science, the numbers of patients surviving complicated diseases are continuously increasing, which in turn leads to elevated chances of anaerobic infections by endogenous bacteria. Traditional growth yield-based antibiotic susceptibility tests (ASTs) against anaerobic bacteria are very time-consuming (≥48 h) and labor intensive, which delays the timely guidance of antibiotic prescription and increases the mortality of patients. Inspired by a fluorescent d-amino acid (FDAA) labeling-based AST (FaAST) that we recently developed for quick determination of aerobic bacteria's susceptibilities, here we report an accurate and fast AST method for anaerobic pathogens. Based on flow cytometry analysis of anaerobes that have been treated with various doses of antibiotics and metabolically labeled with FDAA, the intensities of which can reflect their affected metabolic status by the drugs, the MICs of each drug can then be determined. The whole process can be completed in 5 h. After testing 40 combinations of the representative anaerobic bacteria and antibiotics, our method demonstrates a high susceptibility category accuracy of 95.0%. This FaAST-based protocol is helpful in accurately and quickly guiding antibiotic decisions when treating critical infections caused by anaerobic bacteria.