Screening methods for the detection of antimicrobial resistance genes present in bacterial isolates and the microbiota

Synergizing Nanomaterials and Artificial Intelligence in Advanced Optical Biosensors for Precision Antimicrobial Resistance Diagnosis

Antimicrobial resistance (AMR) poses a critical global One Health concern, ensuing from unintentional and continuous exposure to antibiotics, as well as challenges in accurate contagion diagnostics. Addressing AMR requires a strategic approach that emphasizes early stage prevention through screening in clinical, environmental, farming, and livestock settings to identify nonvulnerable antimicrobial agents and the associated genes. Conventional AMR diagnostics, like antibiotic susceptibility testing, possess drawbacks, including high costs, time-consuming processes, and significant manpower requirements, underscoring the need for intelligent, prompt, and on-site diagnostic techniques. Nanoenabled artificial intelligence (AI)-supported smart optical biosensors present a potential solution by facilitating rapid point-of-care AMR detection with real-time, sensitive, and portable capabilities. This Review comprehensively explores various types of optical nanobiosensors, such as surface plasmon resonance sensors, whispering-gallery mode sensors, optical coherence tomography, interference reflection imaging sensors, surface-enhanced Raman spectroscopy, fluorescence spectroscopy, microring resonance sensors, and optical tweezer biosensors, for AMR diagnostics. By harnessing the unique advantages of these nanoenabled smart biosensors, a revolutionary paradigm shift in AMR diagnostics can be achieved, characterized by rapid results, high sensitivity, portability, and integration with Internet-of-Things (IoT) technologies. Moreover, nanoenabled optical biosensors enable personalized monitoring and on-site detection, significantly reducing turnaround time and eliminating the human resources needed for sample preservation and transportation. Their potential for holistic environmental surveillance further enhances monitoring capabilities in diverse settings, leading to improved modern-age healthcare practices and more effective management of antimicrobial treatments. Embracing these advanced diagnostic tools promises to bolster global healthcare capacity to combat AMR and safeguard One Health.

Assessment of in vitro colistin susceptibility of carbapenem-resistant clinical Gram-negative bacterial isolates using four commercially available systems & Whole-genome sequencing: A diagnostic accuracy study

AIM

To analyze the diagnostic utility of commercially available platforms and Whole-genome sequencing (WGS) for accurate determination of colistin susceptibility test results.

MATERIAL & METHODS

An exploratory diagnostic accuracy study was conducted in which sixty carbapenem-resistant Gram-negative bacteria were subjected to identification and AST using MALDI-TOF MS & MicroScan walkaway 96 Plus. Additional AST was performed using the BD Phoenix system and Mikrolatest colistin kit. The test isolates were subjected to Vitek-2 and WGS at CRL, Bengaluru.

RESULTS

There was no statistically significant agreement between the colistin susceptibility results obtained by WGS, with those of commercial phenotypic platforms. The MicroScan 96 Plus had the highest sensitivity (31 %) & NPV (77 %), and the BD Phoenix system had the highest specificity (97 %) and PPV (50 %), respectively, for determining colistin resistance.

CONCLUSION

The utility of WGS as a tool in AMR surveillance and validation of phenotypic AST methods should be explored further.

Profiling of Antimicrobial Resistance Genes and Integron from Escherichia coli Isolates Using Whole Genome Sequencing

This study is designed to investigate Escherichia coli for the antibiotic resistance genes (ARGs) and integrons from healthy as well as diarrhoeic/diseased animals/birds' faecal samples. A total of eight samples were selected for the study; from each animal, two samples were taken, one from healthy animals/birds and one from diarrhoeic/diseased animals/birds. Antibiotic sensitivity testing (AST) and whole genome sequencing (WGS) was performed for selected isolates. The E. coli isolates showed resistance to moxifloxacin, followed by erythromycin, ciprofloxacin, pefloxacin, tetracycline, levofloxacin, ampicillin, amoxicillin, and sulfadiazine (4/8, 50.00% each). The E. coli isolates were 100% sensitive to amikacin, followed by chloramphenicol, cefixime, cefoperazone, and cephalothin. A total of 47 ARGs from 12 different antibiotic classes were detected among the eight isolates by WGS. The different classes of antibiotics included aminoglycoside, sulphonamide, tetracycline, trimethoprim, quinolone, fosfomycin, phenicol, macrolide, colistin, fosmidomycin, and multidrug efflux. The class 1 integrons were detected in 6/8 (75.00%) isolates with 14 different gene cassettes.

Methodology for laboratory-based antimicrobial resistance surveillance in animals

Antimicrobial resistance (AMR) is a crucial and emerging multifactorial “One Health” problem involving human and animal health, agriculture, aquaculture, and environment; and posing a potential public health hazard globally. The containment of AMR justifies effective surveillance programs to explicate the magnitude of the problem across the contributing sectors. Laboratory-based AMR testing and characterization is the key component of an AMR surveillance program. An AMR surveillance program should have a “top management” for fund mobilization, planning, formulating, and multilateral coordinating of the surveillance activities. The top management should identify competent participating laboratories to form a network comprising a reference laboratory and an adequate number of sentinel laboratories. The responsibilities of the reference laboratory include the development of standardized test methods for ensuring quality and homogeneity of surveillance activities, providing training to the laboratory personnel, and in-depth AMR characterization. The sentinel laboratories will take the responsibilities of receiving samples, isolation and identification of microbes, and initial AMR characterization. The sentinel laboratories will use simple antimicrobial susceptibility test (AST) methods such as disk diffusion tests, whereas the reference laboratories should use automated quantitative AST methods as well as advanced molecular methods to explicit AMR emergence mechanisms. Standard guidelines set by Clinical Laboratory Standards Institute or the European Committee on Antimicrobial Susceptibility Testing, should be followed to bring about conformity and harmonization in the AST procedures. AMR surveillance program in animals is eventually similar to that in human health with the exception is that veterinary antibiotics and veterinary pathogens should be given preference here. Hence, the review study was envisaged to look deep into the structure of the AMR surveillance program with significance on laboratory-based AMR testing and characterization methods.

Monitoring antibiotic resistance genes in wastewater environments: The challenges of filling a gap in the One-Health cycle

Antibiotic resistance (AR) is a global problem requiring international cooperation and coordinated action. Global monitoring must rely on methods available and comparable across nations to quantify AR occurrence and identify sources and reservoirs, as well as paths of AR dissemination. Numerous analytical tools that are gaining relevance in microbiology, have the potential to be applied to AR research. This review summarizes the state of the art of AR monitoring methods, considering distinct needs, objectives and available resources. Based on the overview of distinct approaches that are used or can be adapted to monitor AR, it is discussed the potential to establish reliable and useful monitoring schemes that can be implemented in distinct contexts. This discussion places the environmental monitoring within the One-Health approach, where two types of risk, dissemination across distinct environmental compartments, and transmission to humans, must be considered. The plethora of methodological approaches to monitor AR and the variable features of the monitored sites challenge the capacity of the scientific community and policy makers to reach a common understanding. However, the dialogue between different methods and the production of action-oriented data is a priority. The review aims to warm up this discussion.

The potential of using E. coli as an indicator for the surveillance of antimicrobial resistance (AMR) in the environment

To understand the dynamics of antimicrobial resistance (AMR), in a One-Health perspective, surveillance play an important role. Monitoring systems already exist in the human health and livestock sectors, but there are no environmental monitoring programs. Therefore there is an urgent need to initiate environmental AMR monitoring programs nationally and globally, which will complement existing systems in different sectors. However, environmental programs should not only identify anthropogenic influences and levels of AMR, but they should also allow for identification of transmissions to and from human and animal populations. In the current review we therefore propose using antimicrobial resistant Escherichia coli as indicators for monitoring occurrence and levels of AMR in the environment, including wildlife.

Rapid and Ultrasensitive Detection of Mutations and Genes Relevant to Antimicrobial Resistance in Bacteria

The worldwide emergence of multidrug-resistant (MDR) bacteria is associated with significant morbidity, mortality, and healthcare costs. Rapid and accurate diagnostic methods to detect antibiotic resistance are critical for antibiotic stewardship and infection control measurements. Here a cantilever nanosensor-based diagnostic assay is shown to detect single nucleotide polymorphisms (SNPs) and genes associated with antibiotic resistance in Gram negative (Pseudomonas aeruginosa) and positive (Enterococcus faecium) bacteria, representing frequent causes for MDR infections. Highly specific RNA capture probes for SNPs (ampRD135G or ampRG154R ) or resistance genes (vanA, vanB, and vanD) allow to detect the binding of bacterial RNA within less than 5 min. Serial dilutions of bacterial RNA indicate an unprecedented sensitivity of 10 fg µL-1 total RNA corresponding to less than ten bacterial cells for SNPs and 1 fg µL-1 total RNA for vanD detection equivalent to single bacterial cell sensitivity.

Oxford nanopore sequencing in clinical microbiology and infection diagnostics

Extended turnaround times and large economic costs hinder the usage of currently applied screening methods for bacterial pathogen identification (ID) and antimicrobial susceptibility testing. This review provides an overview of current detection methods and their usage in a clinical setting. Issues of timeliness and cost could soon be circumvented, however, with the emergence of detection methods involving single molecule sequencing technology. In the context of bringing diagnostics closer to the point of care, we examine the current state of Oxford Nanopore Technologies (ONT) products and their interaction with third-party software/databases to assess their capabilities for ID and antimicrobial resistance (AMR) prediction. We outline and discuss a potential diagnostic workflow, enumerating (1) rapid sample prep kits, (2) ONT hardware/software and (3) third-party software and databases to improve the cost, accuracy and turnaround times for ID and AMR. Multiple studies across a range of infection types support that the speed and accuracy of ONT sequencing is now such that established ID and AMR prediction tools can be used on its outputs, and so it can be harnessed for near real time, close to the point-of-care diagnostics in common clinical circumstances.

Typing methods based on whole genome sequencing data

Whole genome sequencing (WGS) of foodborne pathogens has become an effective method for investigating the information contained in the genome sequence of bacterial pathogens. In addition, its highly discriminative power enables the comparison of genetic relatedness between bacteria even on a sub-species level. For this reason, WGS is being implemented worldwide and across sectors (human, veterinary, food, and environment) for the investigation of disease outbreaks, source attribution, and improved risk characterization models. In order to extract relevant information from the large quantity and complex data produced by WGS, a host of bioinformatics tools has been developed, allowing users to analyze and interpret sequencing data, starting from simple gene-searches to complex phylogenetic studies. Depending on the research question, the complexity of the dataset and their bioinformatics skill set, users can choose between a great variety of tools for the analysis of WGS data. In this review, we describe the relevant approaches for phylogenomic studies for outbreak studies and give an overview of selected tools for the characterization of foodborne pathogens based on WGS data. Despite the efforts of the last years, harmonization and standardization of typing tools are still urgently needed to allow for an easy comparison of data between laboratories, moving towards a one health worldwide surveillance system for foodborne pathogens.

Microbiology of hospital wastewater

The study of hospital wastewater (HWW) microbiology is important to understand the pollution load, growth of particular pathogenic microbes, shift and drift in microbial community, development and spread of antibiotic resistance in microbes, and subsequent change in treatment efficiencies. This chapter investigates the potential microbes such as bacteria, viruses, fungi, and parasites present in HWW along with the diseases associated and methods of treatment used. Due to the indiscriminate release of antibiotics from hospitals, HWW serves as a hotspot for emergence of antibiotic-resistance genes (ARGs) and antibiotic-resistance bacteria. This chapter discusses the ARGs occurrence in HWW, their prevalence in the environment, the molecular tools used for identification, and different mechanisms of horizontal gene transfer. Thus better understanding of the microbiology of HWW could further help in development of advanced treatment technologies for effective removal of microbes and their bioproducts (toxins and infectious nucleic acid) from HWW and contaminated water.

Use of whole genome sequencing of commensal Escherichia coli in pigs for antimicrobial resistance surveillance, United Kingdom, 2018

BackgroundSurveillance of commensal Escherichia coli, a possible reservoir of antimicrobial resistance (AMR) genes, is important as they pose a risk to human and animal health. Most surveillance activities rely on phenotypic characterisation, but whole genome sequencing (WGS) presents an alternative.AimIn this retrospective study, we tested 515 E. coli isolated from pigs to evaluate the use of WGS to predict resistance phenotype.MethodsMinimum inhibitory concentration (MIC) was determined for nine antimicrobials of clinical and veterinary importance. Deviation from wild-type, fully-susceptible MIC was assessed using European Committee on Antimicrobial Susceptibility Testing (EUCAST) epidemiological cut-off (ECOFF) values. Presence of AMR genes and mutations were determined using APHA SeqFinder. Statistical two-by-two table analysis and Cohen's kappa (k) test were applied to assess genotype and phenotype concordance.ResultsOverall, correlation of WGS with susceptibility to the nine antimicrobials was 98.9% for test specificity, and 97.5% for the positive predictive value of a test. The overall kappa score (k = 0.914) indicated AMR gene presence was highly predictive of reduced susceptibility and showed excellent correlation with MIC. However, there was variation for each antimicrobial; five showed excellent correlation; four very good and one moderate. Suggested ECOFF adjustments increased concordance between genotypic data and kappa values for four antimicrobials.ConclusionWGS is a powerful tool for accurately predicting AMR that can be used for national surveillance purposes. Additionally, it can detect resistance genes from a wider panel of antimicrobials whose phenotypes are currently not monitored but may be of importance in the future.

Livestock-Associated Methicillin-Resistant Staphylococcus aureus From Animals and Animal Products in the UK

Livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) is an emerging problem in many parts of the world. Although animal-adapted LA-MRSA has been known for many years, recent reports suggest a possible increasing trend in the zoonotic transmission of LA-MRSA in Europe. Since its emergence in the early 2000's, several investigations have indicated that persons in prolonged, repeated contact with affected livestock are at a higher risk of becoming colonized with LA-MRSA. LA-MRSA monitoring in livestock is voluntary under current EU legislation, and not all member states, including the UK, participate. UK LA-MRSA isolates have been detected through scanning surveillance, where samples are submitted from clinically diseased livestock for diagnostic investigation, and research studies. Surveys conducted on retail beef, pig and poultry meat on sale in the UK have also detected LA-MRSA. Taken together these results suggest that LA-MRSA is present in the UK, possibly at low prevalence level, as suggested by available evidence. In this review, we examine the data available from UK livestock and animal products, and make recommendations for future. We also review the findings from whole genome sequencing (WGS) of the possible lineage of some UK livestock isolates.

Proteomics-based discrimination of differentially expressed proteins in antibiotic-sensitive and antibiotic-resistant Salmonella Typhimurium, Klebsiella pneumoniae, and Staphylococcus aureus

This study was designed to compare the differentially expressed proteins between antibiotic-sensitive and antibiotic-resistant Salmonella Typhimurium, Klebsiella pneumonia, and Staphylococcus aureus. The susceptibilities of wild-type (WT), ciprofloxacin (CIP) and/or oxacillin (OXA)-induced, and clinically isolated resistant (CCARM) S. Typhimurium (ST^WT, ST^CIP, and ST^CCARM), K. pneumoniae (KP^WT, KP^CIP, and KP^CCARM), and S. aureus (SA^WT, SA^CIP, SA^OXA, and SA^CCARM) to antibiotics were determined using broth microdilution assay. ST^CIP was highly resistant to piperacillin (MIC > 512 μg/ml), KP^CIP was resistant to chloramphenicol (128 μg/ml) and norfloxacin (16 μg/ml), SA^CIP was resistant to fluoroquinolones (32 μg/ml), and SA^OXA was resistant to ceftriaxone (32 μg/ml). The protein profiles of antibiotic-sensitive and antibiotic-resistant strains were determined using 2-DE analysis followed by LC-MS/MS. The commonly expressed proteins of ST^WT-ST^CIP, ST^WT-ST^CCARM, KP^WT-KP^CIP, KP^WT-KP^CCARM, SA^WT-SA^CIP, SA^WT-SA^OXA, and SA^WT-SA^CCARM were 763, 677, 677, 469, 261, 259, and 226, respectively. The unique protein spots were observed 57 (6.5%), 80 (11.5%), and 68 (13.9%), respectively, for ST^CCARM, KP^CCARM, and SA^CCARM. The highly up-regulated protein, PrsA (10-fold), was observed in ST^CIP resistant to ciprofloxacin (128-fold), levofloxacin (32-fold), norfloxacin (64-fold), and piperacillin (> 16-fold). The up-regulated proteins (YadC, FimA, and RplB) in KP^CIP resistant to chloramphenicol (> 32-fold), ciprofloxacin (32-fold), levofloxacin (6-fold), norfloxacin (128-fold), and sparfloxacin (64-fold). AcrB and RpoB were up-regulated in SA^CCARM resistant to multiple antibiotics. The differentially expressed proteins were related to the antibiotic resistance of ST^WT, ST^CIP, ST^CCARM, KP^WT, KP^CIP, KP^CCARM, SA^WT, SA^CIP, SA^OXA, and SA^CCARM. The resistance-associated proteins could be useful biomarkers for detecting antibiotic-resistant pathogens.

Integrating Whole-Genome Sequencing Data Into Quantitative Risk Assessment of Foodborne Antimicrobial Resistance: A Review of Opportunities and Challenges

Whole-genome sequencing (WGS) will soon replace traditional phenotypic methods for routine testing of foodborne antimicrobial resistance (AMR). WGS is expected to improve AMR surveillance by providing a greater understanding of the transmission of resistant bacteria and AMR genes throughout the food chain, and therefore support risk assessment activities. At this stage, it is unclear how WGS data can be integrated into quantitative microbial risk assessment (QMRA) models and whether their integration will impact final risk estimates or the assessment of risk mitigation measures. This review explores opportunities and challenges of integrating WGS data into QMRA models that follow the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR. We describe how WGS offers an opportunity to enhance the next-generation of foodborne AMR QMRA modeling. Instead of considering all hazard strains as equally likely to cause disease, WGS data can improve hazard identification by focusing on those strains of highest public health relevance. WGS results can be used to stratify hazards into strains with similar genetic profiles that are expected to behave similarly, e.g., in terms of growth, survival, virulence or response to antimicrobial treatment. The QMRA input distributions can be tailored to each strain accordingly, making it possible to capture the variability in the strains of interest while decreasing the uncertainty in the model. WGS also allows for a more meaningful approach to explore genetic similarity among bacterial populations found at successive stages of the food chain, improving the estimation of the probability and magnitude of exposure to AMR hazards at point of consumption. WGS therefore has the potential to substantially improve the utility of foodborne AMR QMRA models. However, some degree of uncertainty remains in relation to the thresholds of genetic similarity to be used, as well as the degree of correlation between genotypic and phenotypic profiles. The latter could be improved using a functional approach based on prediction of microbial behavior from a combination of 'omics' techniques (e.g., transcriptomics, proteomics and metabolomics). We strongly recommend that methodologies to incorporate WGS data in risk assessment be included in any future revision of the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR.

Unveiling the Modulating Role of Extracellular pH in Permeation and Accumulation of Small Molecules in Subcellular Compartments of Gram-negative Escherichia coli using Nonlinear Spectroscopy

Quantitative evaluation of small molecule permeation and accumulation in Gram-negative bacteria is important for drug development against these bacteria. While these measurements are commonly performed at physiological pH, Escherichia coli and many other Enterobacteriaceae infect human gastrointestinal and urinary tracts, where they encounter different pH conditions. To understand how external pH affects permeation and accumulation of small molecules in E. coli cells, we apply second harmonic generation (SHG) spectroscopy using SHG-active antimicrobial compound malachite green as the probe molecule. Using SHG, we quantify periplasmic and cytoplasmic accumulations separately in live E. coli cells, which was never done before. Compartment-wise measurements reveal accumulation of the probe molecule in cytoplasm at physiological and alkaline pH, while entrapment in periplasm at weakly acidic pH and retention in external solution at highly acidic pH. Behind such disparity in localizations, up to 2 orders of magnitude reduction in permeability across the inner membrane at weakly acidic pH and outer membrane at highly acidic pH are found to play key roles. Our results unequivocally demonstrate the control of external pH over entry and compartment-wise distribution of small molecules in E. coli cells, which is a vital information and should be taken into account in antibiotic screening against E. coli and other Enterobacteriaceae members. In addition, our results demonstrate the ability of malachite green as an excellent SHG-indicator of changes of individual cell membrane and periplasm properties of live E. coli cells in response to external pH change from acidic to alkaline. This finding, too, has great importance, as there is barely any other molecular probe that can provide similar information.

Challenges and perspectives in the application of isothermal DNA amplification methods for food and water analysis

Molecular diagnostic tools in the field of food and water quality analysis are becoming increasingly widespread. Usually, based on DNA amplification techniques such as polymerase chain reaction (PCR), these methods are highly sensitive and versatile but require well-equipped laboratories and trained personnel. To reduce analysis time and avoid expensive equipment, isothermal DNA amplification methods for detecting various target organisms have been developed. However, to make molecular diagnostics suitable for low-resource settings and in-field applications, it is crucial to continuously adapt the working steps associated with DNA amplification, namely sample preparation, DNA extraction, and visualization of the results. Many novel approaches have been evaluated in recent years to tackle these challenges, e.g., the use of ionic liquids for the rapid isolation of nucleic acids from organisms relevant for food and water analysis or the integration of entire analytical workflows on microfluidic chips. In any event, the future of applications in the field of isothermal amplification will probably lie in ready-to-use cartridges combined with affordable handheld devices for on-site analysis. This trend article aims to make prospective users more familiar with this technology and its potential for moving molecular diagnostics from the laboratory to the field. Graphical abstract ᅟ.

Molecular Methods for Detection of Antimicrobial Resistance

The increase in bacteria harboring antimicrobial resistance (AMR) is a global problem because there is a paucity of antibiotics available to treat multidrug-resistant bacterial infections in humans and animals. Detection of AMR present in bacteria that may pose a threat to veterinary and public health is routinely performed using standardized phenotypic methods. Molecular methods are often used in addition to phenotypic methods but are set to replace them in many laboratories due to the greater speed and accuracy they provide in detecting the underlying genetic mechanism(s) for AMR. In this article we describe some of the common molecular methods currently used for detection of AMR genes. These include PCR, DNA microarray, whole-genome sequencing and metagenomics, and matrix-assisted laser desorption ionization-time of flight mass spectrometry. The strengths and weaknesses of these methods are discussed, especially in the context of implementing them for routine surveillance activities on a global scale for mitigating the risk posed by AMR worldwide. Based on current popularity and ease of use, PCR and single-isolate whole-genome sequencing seem irreplaceable.