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

β-Galactosidase-triggered in situ synthesis of yellow emitting silicon nanoparticle and its application in visual detection of E. coli O157:H7 and drug susceptibility test

The sensitive detection of foodborne pathogenic and rapid antibiotic susceptibility testing (AST) is of great significance. This paper reports the enzyme-triggered in situ synthesis of yellow emitting silicon nanoparticles (SiNPs) and the detection of Escherichia coli (E. coli) O157:H7 in food samples and the rapid AST. The rapid counting of E. coli O157:H7 has been achieved through direct visual observation, equipment detection, and smartphone digitalization. A simple detection platform based on smartphone senses and cotton swabs has been established. Meanwhile, rapid AST based on enzyme-catalyzed SiNPs can intuitively obtain colorimetric samples. This paper established a system for bacterial enzyme-triggered in situ synthesis of SiNPs, with high responsiveness, luminescence ratio, and specificity. The detection limit for E. coli O157:H7 can reach 100 CFU/mL during 5 h, and the recovery efficiency ranges from 90.14% to 110.16%, which makes it a promising strategy for the rapid detection of E. coli O157:H7 and AST.

Clinical Pilot of Bacterial Transcriptional Profiling as a Combined Genotypic and Phenotypic Antimicrobial Susceptibility Test

Antimicrobial resistance is a growing health threat, but standard methods for determining antibiotic susceptibility are slow and can delay optimal treatment, which is especially consequential in severe infections such as bacteremia. Novel approaches for rapid susceptibility profiling have emerged that characterize either bacterial response to antibiotics (phenotype) or detect specific resistance genes (genotype). GoPhAST-R is a novel assay, performed directly on positive blood cultures, that integrates rapid transcriptional response profiling with detection of key resistance gene transcripts, thereby providing simultaneous data on both phenotype and genotype. Here, we performed the first clinical pilot of GoPhAST-R on 42 positive blood cultures: 26 growing Escherichia coli, 15 growing Klebsiella pneumoniae, and 1 with both. An aliquot of each positive blood culture was exposed to 9 different antibiotics, lysed, then underwent rapid transcriptional profiling on the NanoString® platform; results were analyzed using an in-house susceptibility classification algorithm. GoPhAST-R achieved 95% overall agreement with standard antimicrobial susceptibility testing methods, with the highest agreement for beta-lactams (98%) and the lowest for fluoroquinolones (88%). Epidemic resistance genes including the extended spectrum beta-lactamase bla CTX-M-15 and the carbapenemase bla KPC were also detected within the population. This study demonstrates the clinical feasibility of using transcriptional response profiling for rapid resistance determination, although further validation with larger and more diverse bacterial populations will be essential in future work. GoPhAST-R represents a promising new approach for rapid and comprehensive antibiotic susceptibility testing in clinical settings.

Emerging Biomimetic Sensor Technologies for the Detection of Pathogenic Bacteria: A Commercial Viability Study

Ensuring a rapid and accurate identification of harmful bacteria is crucial in various fields including environmental monitoring, food safety, and clinical diagnostics. Conventional detection methods often suffer from limitations such as long analysis time, complexity, and the need for qualified personnel. Therefore, a lot of research effort is devoted to developing technologies with the potential to revolutionize the detection of pathogenic bacteria by offering rapid, sensitive, and user-friendly platforms for point-of-care analysis. In this light, biosensors have gained significant commercial attention in recent years due to their simplicity, portability, and rapid analysis capabilities. The purpose of this review is to identify a trend by analyzing which biosensor technologies have become commercially successful in the field of bacteria detection. Moreover, we highlight the characteristics that a biosensor must possess to finally arrive in the market and therefore in the hands of the end-user, and we present critical examples of the market applications of various technologies. The aim is to investigate the reason why certain technologies have achieved commercial success and extrapolate these trends to the future economic viability of a new subfield in the world of biosensing: the development of biomimetic sensor platforms. Therefore, an overview of recent advances in the field of biomimetic bacteria detection will be presented, after which the challenges that need to be addressed in the coming years to improve market penetration will be critically evaluated. We will zoom into the current shortcomings of biomimetic sensors based on imprinting technology and aptamers and try to come up with a recommendation for further development based on the trends observed from previous commercial success stories in biosensing.

Urinary tract infections: a review of the current diagnostics landscape

Urinary tract infections are the most common bacterial infections worldwide. Infections can range from mild, recurrent (rUTI) to complicated (cUTIs), and are predominantly caused by uropathogenic Escherichia coli (UPEC). Antibiotic therapy is important to tackle infection; however, with the continued emergence of antibiotic resistance there is an urgent need to monitor the use of effective antibiotics through better stewardship measures. Currently, clinical diagnosis of UTIs relies on empiric methods supported by laboratory testing including cellular analysis (of both human and bacterial cells), dipstick analysis and phenotypic culture. Therefore, development of novel, sensitive and specific diagnostics is an important means to rationalise antibiotic therapy in patients. This review discusses the current diagnostic landscape and highlights promising novel diagnostic technologies in development that could aid in treatment and management of antibiotic-resistant UTIs.

Rapid Antifungal Susceptibility Testing Based on Single-Cell Metabolism Analysis Using Stimulated Raman Scattering Imaging

Rapid antifungal susceptibility testing (AFST) is urgently needed in clinics to treat invasive fungal infections with the appropriate antifungal drugs and to slow the emergence of antifungal resistance. However, current AFST methods are time-consuming (24-48 h) due to the slow growth of fungal cells and the methods not being able to work directly for clinical samples. Here, we demonstrate rapid AFST by measuring the metabolism in single fungal cells using stimulated Raman scattering imaging and deuterium probing. Distinct metabolic responses were observed in Candida albicans to different classes of antifungal drugs: while the metabolism was inhibited by amphotericin B, it was stimulated by azoles (fluconazole and voriconazole) and micafungin. Accordingly, we propose metabolism change as a biomarker for rapid AFST. The results were obtained in 4 h with 100% categorical agreement with the gold standard broth microdilution test. In addition, a protocol was developed for direct AFST from positive blood cultures. This method overcomes the limitation of slow growth in conventional methods and has the potential for the rapid diagnosis of candidemia and other clinical fungal infections.

Phase Contrast Image-Based Rapid Antimicrobial Susceptibility Testing of Bacteria in Liquid Culture Media

Currently, the world is facing the problem of bacterial resistance, which threatens public health, and bacterial antimicrobial susceptibility testing (AST) plays an important role in biomedicine, dietary safety and aquaculture. Traditional AST methods take a long time, usually 16-24 h, and cannot meet the demand for rapid diagnosis in the clinic, so rapid AST methods are needed to shorten the detection time. In this study, by using an in-house built centrifuge to centrifuge bacteria in a liquid medium onto the inner wall of the bottom surface of a counting plate, and using a phase contrast microscope to track bacterial growth under the effect of different antibiotic concentrations, the results of the minimum inhibitory concentration (MIC) of bacteria under the effect of antibiotics can be obtained in as early as 4 h. We used a combination of E. coli and tigecycline and obtained MIC results that were consistent with those obtained using the gold standard broth micro-dilution method, demonstrating the validity of our method; due to the time advantage, the complete set can be used in the future for point of care and clinical applications, helping physicians to quickly obtain the MIC used to inhibit bacterial growth.

Comparison of Different Label-Free Raman Spectroscopy Approaches for the Discrimination of Clinical MRSA and MSSA Isolates

Methicillin-resistant Staphylococcus aureus (MRSA) is classified as one of the priority pathogens that threaten human health. Resistance detection with conventional microbiological methods takes several days, forcing physicians to administer empirical antimicrobial treatment that is not always appropriate. A need exists for a rapid, accurate, and cost-effective method that allows targeted antimicrobial therapy in limited time. In this pilot study, we investigate the efficacy of three different label-free Raman spectroscopic approaches to differentiate methicillin-resistant and -susceptible clinical isolates of S. aureus (MSSA). Single-cell analysis using 532 nm excitation was shown to be the most suitable approach since it captures information on the overall biochemical composition of the bacteria, predicting 87.5% of the strains correctly. UV resonance Raman microspectroscopy provided a balanced accuracy of 62.5% and was not sensitive enough in discriminating MRSA from MSSA. Excitation of 785 nm directly on the petri dish provided a balanced accuracy of 87.5%. However, the difference between the strains was derived from the dominant staphyloxanthin bands in the MRSA, a cell component not associated with the presence of methicillin resistance. This is the first step toward the development of label-free Raman spectroscopy for the discrimination of MRSA and MSSA using single-cell analysis with 532 nm excitation. IMPORTANCE Label-free Raman spectra capture the high chemical complexity of bacterial cells. Many different Raman approaches have been developed using different excitation wavelength and cell analysis methods. This study highlights the major importance of selecting the most suitable Raman approach, capable of providing spectral features that can be associated with the cell mechanism under investigation. It is shown that the approach of choice for differentiating MRSA from MSSA should be single-cell analysis with 532 nm excitation since it captures the difference in the overall biochemical composition. These results should be taken into consideration in future studies aiming for the development of label-free Raman spectroscopy as a clinical analytical tool for antimicrobial resistance determination.

Compound Raman microscopy for rapid diagnosis and antimicrobial susceptibility testing of pathogenic bacteria in urine

Rapid identification and antimicrobial susceptibility testing (AST) of bacteria are key interventions to curb the spread and emergence of antimicrobial resistance. The current gold standard identification and AST methods provide comprehensive diagnostic information but often take 3 to 5 days. Here, a compound Raman microscopy (CRM), which integrates Raman spectroscopy and stimulated Raman scattering microscopy in one system, is presented and demonstrated for rapid identification and AST of pathogens in urine. We generated an extensive bacterial Raman spectral dataset and applied deep learning to identify common clinical bacterial pathogens. In addition, we employed stimulated Raman scattering microscopy to quantify bacterial metabolic activity to determine their antimicrobial susceptibility. For proof-of-concept, we demonstrated an integrated assay to diagnose urinary tract infection pathogens, S. aureus and E. coli. Notably, the CRM system has the unique ability to provide Gram-staining classification and AST results within ~3 h directly from urine samples and shows great potential for clinical applications.

Rapid Antibiotic Susceptibility Testing by Deuterium Labeling of Bacterial Lipids in On-Target Microdroplet Cultures

Antimicrobial resistance is a serious challenge facing human and veterinary health. Current methods of detecting resistance are limited in turn-around time or universal detection. In this work, a new antimicrobial susceptibility test is developed and validated, which utilizes deuterium labeling of membrane lipids to track the growth of bacterial cells. We hypothesize that deuterium uptake and subsequent labeling of lipids can be detected using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). Additionally, bacteria growth is performed on the MALDI target, minimizing sample preparation materials and time. When two Escherichia coli strains are grown in the presence of deuterium oxide, labeling can be detected in as little as 30 min to 2 h. The labeling efficiency, or the ratio of labeled to unlabeled lipid peaks, provides information about the growth rate of bacteria. This growth ratio can differentiate between resistant and susceptible strains of bacteria as a resistant strain will maintain ∼50% labeling efficiency between untreated and treated cultures. In comparison, a susceptible strain will see a decrease in fractional abundance of deuterium from ∼50% in the untreated to ∼10% in the treated. This approach is applied to measure the minimum inhibitory concentration (MIC) of the resistant and susceptible strains from on-target microdroplet culture in a range of antibiotic concentrations. The first antibiotic concentration with a significant decrease in fractional abundance of deuterium correlates well with a traditionally obtained MIC using broth dilution, indicating the clinical relevance of the results.

Discrimination of Methicillin-resistant Staphylococcus aureus by MALDI-TOF Mass Spectrometry with Machine Learning Techniques in Patients with Staphylococcus aureus Bacteremia

Early administration of proper antibiotics is considered to improve the clinical outcomes of Staphylococcus aureus bacteremia (SAB), but routine clinical antimicrobial susceptibility testing takes an additional 24 h after species identification. Recent studies elucidated matrix-assisted laser desorption/ionization time-of-flight mass spectra to discriminate methicillin-resistant strains (MRSA) or even incorporated with machine learning (ML) techniques. However, no universally applicable mass peaks were revealed, which means that the discrimination model might need to be established or calibrated by local strains’ data. Here, a clinically feasible workflow was provided. We collected mass spectra from SAB patients over an 8-month duration and preprocessed by binning with reference peaks. Machine learning models were trained and tested by samples independently of the first six months and the following two months, respectively. The ML models were optimized by genetic algorithm (GA). The accuracy, sensitivity, specificity, and AUC of the independent testing of the best model, i.e., SVM, under the optimal parameters were 87%, 75%, 95%, and 87%, respectively. In summary, almost all resistant results were truly resistant, implying that physicians might escalate antibiotics for MRSA 24 h earlier. This report presents an attainable method for clinical laboratories to build an MRSA model and boost the performance using their local data.

A Review of Raman-Based Technologies for Bacterial Identification and Antimicrobial Susceptibility Testing

Antimicrobial resistance (AMR) is a global medical threat that seriously endangers human health. Rapid bacterial identification and antimicrobial susceptibility testing (AST) are key interventions to combat the spread and emergence of AMR. Although current clinical bacterial identification and AST provide comprehensive information, they are labor-intensive, complex, inaccurate, and slow (requiring several days, depending on the growth of pathogenic bacteria). Recently, Raman-based identification and AST technologies have played an increasingly important role in fighting AMR. This review summarizes major Raman-based techniques for bacterial identification and AST, including spontaneous Raman scattering, surface-enhanced Raman scattering (SERS), and coherent Raman scattering (CRS) imaging. Then, we discuss recent developments in rapid identification and AST methods based on Raman technology. Finally, we highlight the major challenges and potential future efforts to improve clinical outcomes through rapid bacterial identification and AST.

Electrochemical Sensors for Antibiotic Susceptibility Testing: Strategies and Applications

Increasing awareness of the impacts of infectious diseases has driven the development of advanced techniques for detecting pathogens in clinical and environmental settings. However, this process is hindered by the complexity and variability inherent in antibiotic-resistant species. A great deal of effort has been put into the development of antibiotic-resistance/susceptibility testing (AST) sensors and systems to administer proper drugs for patient-tailored therapy. Electrochemical sensors have garnered increasing attention due to their powerful potential to allow rapid, sensitive, and real-time monitoring, alongside the low-cost production, feasibility of minimization, and easy integration with other techniques. This review focuses on the recent advances in electrochemical sensing strategies that have been used to determine the level of antibiotic resistance/susceptibility of pathogenic bacteria. The recent examples of the current electrochemical AST sensors discussed here are classified into four categories according to what is detected and quantitated: the presence of antibiotic-resistant genes, changes in impedance caused by cell lysis, current response caused by changes in cellular membrane properties, and changes in the redox state of redox molecules. It also discusses potential strategies for the development of electrochemical AST sensors, with the goal of broadening their practical applications across various scientific and technological fields.

Recent Advances in Rapid Antimicrobial Susceptibility Testing

Background

Antimicrobial susceptibility testing (AST) is classically performed using growth-based techniques that essentially require viable bacterial matter to become visible to the naked eye or a sophisticated densitometer.

Content

Technologies based on the measurement of bacterial density in suspension have evolved marginally in accuracy and rapidity over the 20th century, but assays expanded for new combinations of bacteria and antimicrobials have been automated, and made amenable to high-throughput turn-around. Over the past 25 years, elevated AST rapidity has been provided by nucleic acid-mediated amplification technologies, proteomic and other “omic” methodologies, and the use of next-generation sequencing. In rare cases, AST at the level of single-cell visualization was developed. This has not yet led to major changes in routine high-throughput clinical microbiological detection of antimicrobial resistance.

Summary

We here present a review of the new generation of methods and describe what is still urgently needed for their implementation in day-to-day management of the treatment of infectious diseases.

Current Scenario and Challenges in the Direct Identification of Microorganisms Using MALDI TOF MS

MALDI TOF MS-based microbial identification significantly lowers the operational costs because of minimal requirements of substrates and reagents for extraction. Therefore, it has been widely used in varied applications such as clinical, food, military, and ecological research. However, the MALDI TOF MS method is laced with many challenges including its limitation of the reference spectrum. This review briefly introduces the background of MALDI TOF MS technology, including sample preparation and workflow. We have primarily discussed the application of MALDI TOF MS in the identification of microorganisms. Furthermore, we have discussed the current trends for bioaerosol detection using MALDI TOF MS and the limitations and challenges involved, and finally the approaches to overcome these challenges.