Phenotypic antibiotic susceptibility testing of pathogenic bacteria using photonic readout methods: recent achievements and impact

Platinum nanoparticles-based electrochemical H2O2 sensor for rapid antibiotic susceptibility testing

With the increase of antimicrobial resistance, rapid antibiotic susceptibility testing (AST) to guide precise antibiotic administration has become increasingly important. However, current gold standard AST approaches tend to take up to 24-48 h. In this work, based on the nature of catalase-positive bacteria decomposing H2O2, we developed a rapid, portable, straightforward, and cost-effective phenotypic AST approach by detecting residual H2O2 using a Pt nanoparticles-based electrochemical sensor. The pulse current of the sensor exhibited a linear increase with rising H2O2 concentration, demonstrating a high sensitivity of ∼382.2 μA cm-2 mM-1. This approach showed superb diagnostic performance, with an area under the curve of 1 for 24 clinical samples of Escherichia coli and Staphylococcus aureus, with a total detection time of 60 and 45 min, respectively. Furthermore, the performance of the sensor showed no degradation even after 100 detections, promising a substantial reduction in AST costs. Overall, the proposed approach exhibited immense potential for diagnosing bacterial antibiotic resistance.

Multipad agarose plate: a rapid and high-throughput approach for antibiotic susceptibility testing

We describe a phenotypic antibiotic susceptibility testing (AST) method that can provide an eightfold speed-up in turnaround time compared with the current clinical standard by leveraging advances in microscopy and single-cell imaging. A newly developed growth plate containing 96 agarose pads, termed the multipad agarose plate (MAP), can be assembled at low cost. Pads can be prepared with dilution series of antibiotics. Bacteria are seeded on the pads and automatically imaged using brightfield microscopy, with a fully automated segmentation pipeline quantifying microcolony formation and growth rate. Using a test set of nine antibiotics with very different targets, we demonstrate that accurate minimum inhibitory concentration (MIC) measurements can be performed based on the growth rate of microcolonies within 3 h of incubation with the antibiotic when started from exponential phase. Faster, reliable and high-throughput methods for AST, such as MAP, could improve patient care by expediting treatment initiation and alleviating the burden of antimicrobial resistance.

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.

Identification of bacteria in mixed infection from urinary tract of patient's samples using Raman analysis of dried droplets

Urinary tract infections (UTI) are among the most frequent nosocomial infections. A fast identification of the pathogen and assignment of Gram type could help to prescribe most suitable treatments. Raman spectroscopy holds high potential for fast and reliable bacterial pathogens identification. While most studies so far have focused on individual pathogens or artificial mixtures, this contribution aims to translate the analysis to primary urine samples from patients with suspected UTIs. For this, we have included 59 primary urine samples out of which 29 were diagnosed as mixed infections. For Raman analysis, we first trained two classification models based on principal component analysis - linear discriminant analysis (PCA-LDA) with more than 3500 Raman spectra of 85 clinical isolates from 23 species in order to (1) identify the Gram type of the bacteria and (2) assign family membership to one of the six most abundant bacterial families in urinary tract infections (Enterobacteriaceae, Morganellaceae, Pseudomonadaceae, Enterococcaceae, Staphylococcaceae and Streptococcaceae). The classification models were applied to artificial mixtures of Gram positive and Gram negative bacteria to correctly predict mixed infections with an accuracy of 75%. Raman scans of dried droplets did not yet yield optimal classification results on family level. When translating the method to primary urine samples, we observed a strong bias towards Gram negative bacteria, on family level towards Morganellaceae, which reduced prediction accuracy. Spectral differences were observed between isolates grown on standard growth medium and bacteria of the same strain when characterized directly from the patient. Thus, improvement of the classification accuracy is expected with a larger data base containing also bacteria measured directly from the urine sample.

Rapid antimicrobial susceptibility testing for low bacterial concentrations integrating a centrifuge based bacterial cell concentrator

Antibiotic resistance threatens human health worldwide. Patients infected with antibiotic-resistant bacteria require appropriate antibiotic prescriptions based on a rapid antibiotic susceptibility test (AST). Various rapid AST methods have been developed to replace the conventional AST method, which requires a long testing time. However, in most cases, these methods require a high density of bacterial samples, which leads to an additional incubation or concentration process. In this study, we introduce a rapid AST platform that allows the use of low-density bacterial samples by concentrating bacterial cells and performing AST on a single microfluidic chip. In addition, the outlet-free loading process enables the platform to load the sample and concentrate bacteria into a small field of view for single-cell detection. Using this method, rapid AST determined antibiotic resistance in three hours from a standard strain of 10³ colony-forming unit (CFU) per ml bacterial concentration. This technique can be used for the cell-based drug testing of various low-concentration bacterial samples.

Rapid Detection of MCR-Mediated Colistin Resistance in Escherichia coli

Colistin is one of the last-resort antibiotics for infections caused by multidrug-resistant Gram-negative bacteria. However, the wide spread of novel plasmid-carrying colistin resistance genes mcr-1 and its variants substantially compromise colistin's therapeutic effectiveness and pose a severe danger to public health. To detect colistin-resistant microorganisms induced by mcr genes, rapid and reliable antibiotic susceptibility testing (AST) is imminently needed. In this study, we identified an RNA-based AST (RBAST) to discriminate between colistin-susceptible and mcr-1-mediated colistin-resistant bacteria. After short-time colistin treatment, RBAST can detect differentially expressed RNA biomarkers in bacteria. Those candidate mRNA biomarkers were successfully verified within colistin exposure temporal shifts, concentration shifts, and other mcr-1 variants. Furthermore, a group of clinical strains were effectively distinguished by using the RBAST approach during the 3-h test duration with over 93% accuracy. Taken together, our findings imply that certain mRNA transcripts produced in response to colistin treatment might be useful indicators for the development of fast AST for mcr-positive bacteria.

IMPORTANCE The emergence and prevalence of mcr-1 and its variants in humans, animals, and the environment pose a global public health threat. There is a pressing urgency to develop rapid and accurate methods to identify MCR-positive colistin-resistant bacteria in the clinical samples, providing a basis for subsequent effective antibiotic treatment. Using the specific mRNA signatures, we develop an RNA-based antibiotic susceptibility testing (RBAST) for effectively distinguishing colistin-susceptible and mcr-1-mediated colistin-resistant strains. Meanwhile, the detection efficiency of these RNA biomarkers was evidenced in other mcr variants-carrying strains. By comparing with the traditional AST method, the RBAST method was verified to successfully characterize a set of clinical isolates during 3 h assay time with over 93% accuracy. Our study provides a feasible method for the rapid detection of colistin-resistant strains in clinical practice.

Biochemical Analysis of Leukocytes after In Vitro and In Vivo Activation with Bacterial and Fungal Pathogens Using Raman Spectroscopy

Biochemical information from activated leukocytes provide valuable diagnostic information. In this study, Raman spectroscopy was applied as a label-free analytical technique to characterize the activation pattern of leukocyte subpopulations in an in vitro infection model. Neutrophils, monocytes, and lymphocytes were isolated from healthy volunteers and stimulated with heat-inactivated clinical isolates of Candida albicans, Staphylococcus aureus, and Klebsiella pneumoniae. Binary classification models could identify the presence of infection for monocytes and lymphocytes, classify the type of infection as bacterial or fungal for neutrophils, monocytes, and lymphocytes and distinguish the cause of infection as Gram-negative or Gram-positive bacteria in the monocyte subpopulation. Changes in single-cell Raman spectra, upon leukocyte stimulation, can be explained with biochemical changes due to the leukocyte’s specific reaction to each type of pathogen. Raman spectra of leukocytes from the in vitro infection model were compared with spectra from leukocytes of patients with infection (DRKS-ID: DRKS00006265) with the same pathogen groups, and a good agreement was revealed. Our study elucidates the potential of Raman spectroscopy-based single-cell analysis for the differentiation of circulating leukocyte subtypes and identification of the infection by probing the molecular phenotype of those cells.

Fast Antibiotic Susceptibility Testing via Raman Microspectrometry on Single Bacteria: An MRSA Case Study

Despite recent advances in molecular diagnostics, ultrafast determination of the antibiotic susceptibility phenotype of pathogenic microorganisms is still a major challenge of in vitro diagnostics (IVD) of infectious diseases. Raman microspectroscopy has been proposed as a means to achieve this goal. Previous studies have shown that susceptibility phenotyping could be done through Raman analysis of microbial cells, either in large clusters or down to the single-cell level in the case of Gram-negative rods. Gram-positive cocci such as Staphylococcus aureus pose several challenges due to their size and their different metabolic and chemical characteristics. Using a tailored automated single-cell Raman spectrometer and a previously proposed sample preparation protocol, we acquired and analyzed 9429 S. aureus single cells belonging to three cefoxitin-resistant strains and two susceptible strains during their incubation in the presence of various concentrations of cefoxitin. We observed an effect on S. aureus spectra that is weaker than what was detected on previous bacteria/drug combinations, with a higher cell-to-cell response variability and an important impact of incubation conditions on the phenotypic resistance of a given strain. Overall, the proposed protocol was able to correlate strains' phenotype with a specific modification of the spectra using majority votes. We, hence, confirm that our previous results on single-cell Raman antibiotic susceptibility testing can be extended to the S. aureus case and further clarify potential limitations and development requirements of this approach in the move toward industrial applications.

Diffusion-Convection Hybrid Microfluidic Platform for Rapid Antibiotic Susceptibility Testing

Conventional antibiotic susceptibility testing (AST) assays such as broth microdilution and Kirby-Bauer disk diffusion are time-consuming (e.g., 24-72 h) and labor-intensive. Here, we present a microfluidic platform to perform AST assays with a broad range of antibiotic concentrations and controls. A culture medium stream was serially enriched with antibiotics along the length of the platform via diffusion and flow-directing mass convection mechanisms, generating a concentration gradient captured in a series of microchamber duplicates. We observed an agreement between the simulated and experimental concentration gradients and applicability to a variety of different molecules by changing the loading time according to a simple linear equation. The AST assay in our platform is based on bacterial metabolism, indicated by resazurin fluorescence. The small reaction volume enabled a minimum inhibitory concentration (MIC) to be determined in 4-5 h. Proof-of-concept functionality testing, using human isolates and clinically important antibiotics from different classes, indicated a high rate of agreement (94%: MIC within ±1 two-fold dilution of the reference method) of on-chip MICs and conventional broth microdilution. Overall, our results showed that this microfluidic platform is capable of determining antibiotic susceptibility in a rapid and reliable manner.

Recent Development of Rapid Antimicrobial Susceptibility Testing Methods through Metabolic Profiling of Bacteria

Due to the inappropriate use and overuse of antibiotics, the emergence and spread of antibiotic-resistant bacteria are increasing and have become a major threat to human health. A key factor in the treatment of bacterial infections and slowing down the emergence of antibiotic resistance is to perform antimicrobial susceptibility testing (AST) of infecting bacteria rapidly to prescribe appropriate drugs and reduce the use of broad-spectrum antibiotics. Current phenotypic AST methods based on the detection of bacterial growth are generally reliable but are too slow. There is an urgent need for new methods that can perform AST rapidly. Bacterial metabolism is a fast process, as bacterial cells double about every 20 to 30 min for fast-growing species. Moreover, bacterial metabolism has shown to be related to drug resistance, so a comparison of differences in microbial metabolic processes in the presence or absence of antimicrobials provides an alternative approach to traditional culture for faster AST. In this review, we summarize recent developments in rapid AST methods through metabolic profiling of bacteria under antibiotic treatment.

Affordable automated phenotypic antibiotic susceptibility testing method based on a contactless conductometric sensor

User-friendly phenotypic antibiotic susceptibility testing (AST) methods are urgently needed in many fields including clinical medicine, epidemiological studies and drug research. Herein, we report a convenient and cost-effective phenotypic AST method based on online monitoring bacterial growth with a developed 8-channel contactless conductometric sensor (CCS). Using E. coli and V. parahaemolyticus as microorganism models, as well as enoxacin, florfenicol, ampicillin, kanamycin and sulfadiazine as antibiotic probes. The minimum inhibitory concentration (MIC) determination was validated in comparison with standard broth microdilution (BMD) assay. The total essential agreements between the CCS AST assays and the reference BMD AST assays are 68.8–92.3%. The CCS has an approximate price of $9,000 (USD). Requiring neither chemical nor biotic auxiliary materials for the assay makes the cost of each sample < $1. The MICs obtained with the automated CCS AST assays are more precise than those obtained with the manual BMD. Moreover, in 72 percent of the counterpart, the MICs obtained with the CCS AST assays are higher than that obtained with the BMD AST assays. The proposed CCS AST method has advantages in affordability, accuracy, sensitivity and user-friendliness.

Automated and rapid identification of multidrug resistant Escherichia coli against the lead drugs of acylureidopenicillins, cephalosporins, and fluoroquinolones using specific Raman marker bands

A Raman-based, strain-independent, semi-automated method is presented that allows the rapid (<3 hours) determination of antibiotic susceptibility of bacterial pathogens isolated from clinical samples. Applying a priori knowledge about the mode of action of the respective antibiotic, we identified characteristic Raman marker bands in the spectrum and calculated batch-wise weighted sum scores from standardized Raman intensity differences between spectra of antibiotic exposed and nonexposed samples of the same strains. The lead substances for three relevant antibiotic classes (fluoroquinolone ciprofloxacin, third-generation cephalosporin cefotaxime, ureidopenicillin piperacillin) against multidrug-resistant Gram-negative bacteria (MRGN) revealed a high sensitivity and specificity for the susceptibility testing of two Escherichia coli laboratory strains and 12 clinical isolates. The method benefits from the parallel incubation of control and treated samples, which reduces the variance due to alterations in cultivation conditions and the standardization of differences between batches leading to long-term comparability of Raman measurements.

Innovative and rapid antimicrobial susceptibility testing systems

Antimicrobial resistance (AMR) is a major threat to human health worldwide, and the rapid detection and quantification of resistance, combined with antimicrobial stewardship, are key interventions to combat the spread and emergence of AMR. Antimicrobial susceptibility testing (AST) systems are the collective set of diagnostic processes that facilitate the phenotypic and genotypic assessment of AMR and antibiotic susceptibility. Over the past 30 years, only a few high-throughput AST methods have been developed and widely implemented. By contrast, several studies have established proof of principle for various innovative AST methods, including both molecular-based and genome-based methods, which await clinical trials and regulatory review. In this Review, we discuss the current state of AST systems in the broadest technical, translational and implementation-related scope.

Rapid Antimicrobial Susceptibility Testing of Patient Urine Samples Using Large Volume Free-Solution Light Scattering Microscopy

The emergence of antibiotic resistance has prompted the development of rapid antimicrobial susceptibility testing (AST) technologies that will enable evidence-based treatment and promote antimicrobial stewardship. To date, many rapid AST methods have been developed, but few are able to be performed on clinical samples directly. Here we developed a large volume light scattering microscopy technique that tracks phenotypic features of single bacterial cells directly in clinical urine samples without sample enrichment or culturing. The technique demonstrated rapid (90 min) detection of Escherichia coli in 24 clinical urine samples with 100% sensitivity and 83% specificity and rapid (90 min) AST in 12 urine samples with 87.5% categorical agreement with two antibiotics, ampicillin and ciprofloxacin.