Direct Antimicrobial Susceptibility Testing on Clinical Urine Samples by Optical Tracking of Single Cell Division Events

Blood culture-free ultra-rapid antimicrobial susceptibility testing

Treatment assessment and patient outcome for sepsis depend predominantly on the timely administration of appropriate antibiotics1-3. However, the clinical protocols used to stratify and select patient-specific optimal therapy are extremely slow4. In particular, the major hurdle in performing rapid antimicrobial susceptibility testing (AST) remains in the lengthy blood culture procedure, which has long been considered unavoidable due to the limited number of pathogens present in the patient's blood. Here we describe an ultra-rapid AST method that bypasses the need for traditional blood culture, thereby demonstrating potential to reduce the turnaround time of reporting drug susceptibility profiles by more than 40-60 h compared with hospital AST workflows. Introducing a synthetic beta-2-glycoprotein I peptide, a broad range of microbial pathogens are selectively recovered from whole blood, subjected to species identification or instantly proliferated and phenotypically evaluated for various drug conditions using a low-inoculum AST chip. The platform was clinically evaluated by the enrolment of 190 hospitalized patients suspected of having infection, achieving 100% match in species identification. Among the eight positive cases, six clinical isolates were retrospectively tested for AST showing an overall categorical agreement of 94.90% with an average theoretical turnaround time of 13 ± 2.53 h starting from initial blood processing.

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.

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.

Accurate Prediction of Antimicrobial Susceptibility for Point-of-Care Testing of Urine in Less than 90 Minutes via iPRISM Cassettes

The extensive and improper use of antibiotics has led to a dramatic increase in the frequency of antibiotic resistance among human pathogens, complicating infectious disease treatments. In this work, a method for rapid antimicrobial susceptibility testing (AST) is presented using microstructured silicon diffraction gratings integrated into prototype devices, which enhance bacteria-surface interactions and promote bacterial colonization. The silicon microstructures act also as optical sensors for monitoring bacterial growth upon exposure to antibiotics in a real-time and label-free manner via intensity-based phase-shift reflectometric interference spectroscopic measurements (iPRISM). Rapid AST using clinical isolates of Escherichia coli (E. coli) from urine is established and the assay is applied directly on unprocessed urine samples from urinary tract infection patients. When coupled with a machine learning algorithm trained on clinical samples, the iPRISM AST is able to predict the resistance or susceptibility of a new clinical sample with an Area Under the Receiver Operating Characteristic curve (AUC) of ∼ 0.85 in 1 h, and AUC > 0.9 in 90 min, when compared to state-of-the-art automated AST methods used in the clinic while being an order of magnitude faster.

Moving microcapillary antibiotic susceptibility testing (mcAST) towards the clinic: unravelling kinetics of detection of uropathogenic E. coli, mass-manufacturing and usability for detection of urinary tract infections in human urine

Innovation in infection based point-of-care (PoC) diagnostics is vital to avoid unnecessary use of antibiotics and the development of antimicrobial resistance. Several groups including our research team have in recent years successfully miniaturised phenotypic antibiotic susceptibility tests (AST) of isolated bacterial strains, providing validation that miniaturised AST can match conventional microbiological methods. Some studies have also shown the feasibility of direct testing (without isolation or purification), specifically for urinary tract infections, paving the way for direct microfluidic AST systems at PoC. As rate of bacteria growth is intrinsically linked to the temperature of incubation, transferring miniaturised AST nearer the patient requires building new capabilities in terms of temperature control at PoC, furthermore widespread clinical use will require mass-manufacturing of microfluidic test strips and direct testing of urine samples. This study shows for the first-time application of microcapillary antibiotic susceptibility testing (mcAST) directly from clinical samples, using minimal equipment and simple liquid handling, and with kinetics of growth recorded using a smartphone camera. A complete PoC-mcAST system was presented and tested using 12 clinical samples sent to a clinical laboratory for microbiological analysis. The test showed 100% accuracy for determining bacteria in urine above the clinical threshold (5 out of 12 positive) and achieved 95% categorical agreement for 5 positive urines tested with 4 antibiotics (nitrofurantoin, ciprofloxacin, trimethoprim and cephalexin) within 6 h compared to the reference standard overnight AST method. A kinetic model is presented for metabolization of resazurin, demonstrating kinetics of degradation of resazurin in microcapillaries follow those observed for a microtiter plate, with time for AST dependent on the initial CFU ml^-1 of uropathogenic bacteria in the urine sample. In addition, we show for the first time that use of air-drying for mass-manufacturing and deposition of AST reagents within the inner surface of mcAST strips matches results obtained with standard AST methods. These results take mcAST a step closer to clinical application, for example as PoC support for antibiotic prescription decisions within a day.

Bioinspired Plasmonic Nanosensor for on-Site Antimicrobial Susceptibility Testing in Urine Samples

Delayed use of appropriate antibiotics for superbugs, particularly for extended-spectrum β-lactamase (ESBL)-producing Escherichia coli (E. coli) and Klebsiella pneumoniae (K. pn), has caused extensive morbidity and mortality worldwide. Therefore, rapid and on-site antimicrobial susceptibility testing (AST) is urgently required. Unfortunately, currently, no phenotypic AST can realize a sample-to-answer result within 2 h directly from a clinical sample and without using laboratory equipment or customized devices. Inspired by observing that E. coli and K. pn can rapidly catalyze H₂O₂, we developed a plasmonic nanosensor that responds to the proliferation of bacteria for realizing rapid AST. The results can be determined with the naked eye, digitized using a smartphone, and validated using ultraviolet-visible spectrometry. Our assay achieved superb area under the curves of 0.9752 and 1 in a receiver operating characteristic analysis directly obtained from uncultured clinical urine samples infected by E. coli and K. pn, respectively. The entire process from sample collection to analysis takes 100 min for E. coli and 85 min for K. pn detection. Our platform provides a practical approach for performing on-site AST in clinics to improve the survival of patients. It releases the burden of superbugs and avoids the abuse of antibiotics.

Combinatorial screening SlipChip for rapid phenotypic antimicrobial susceptibility testing

Antimicrobial resistance (AMR) by bacteria is a serious global threat, and a rapid, high-throughput, and easy-to-use phenotypic antimicrobial susceptibility testing (AST) method is essential for making timely treatment decisions and controlling the spread of antibiotic resistant micro-organisms. Traditional culture-based methods are time-consuming, and their capability to screen against a large number of different conditions is limited; meanwhile genotypic based methods, including sequencing and PCR based methods, are constrained by rarely identified resistance genes and complicated resistance mechanisms. Here, a combinatorial-screening SlipChip (cs-SlipChip) containing 192 nanoliter-sized compartments is developed which can perform high-throughput phenotypic AST within three hours by monitoring the bacterial growth within nanoliter-sized droplets with bright-field imaging and analyzing the changes in bacterial number and morphology. The minimum inhibitory concentration (MIC) of Escherichia coli ATCC 25922 against four antibiotics (ampicillin, ciprofloxacin, ceftazidime, and nitrofurantoin) can be measured in one chip within 3 hours. Furthermore, five antibiotic-resistant E. coli strains were isolated from patients diagnosed with urinary tract infections (UTIs), and an individual isolate was tested using four antibiotics and eleven antibiotic combinations simultaneously with three different concentrations of each. The results from the cs-SlipChip agree with those of a VITEK 2 automated system. This cs-SlipChip provides a practical high-throughput and rapid phenotypic method for AST and can also be used to screen different chemicals and antibiotic combinations for the treatment of multiple antibiotic-resistant bacteria.

Rapid Detection of Urinary Tract Infection in 10 min by Tracking Multiple Phenotypic Features in a 30 s Large-Volume Scattering Video of Urine Microscopy

Rapid point-of-care (POC) diagnosis of bacterial infection diseases provides clinical benefits of prompt initiation of antimicrobial therapy and reduction of the overuse/misuse of unnecessary antibiotics for nonbacterial infections. We present here a POC compatible method for rapid bacterial infection detection in 10 min. We use a large-volume solution scattering imaging (LVSi) system with low magnifications (1-2×) to visualize bacteria in clinical samples, thus eliminating the need for culture-based isolation and enrichment. We tracked multiple intrinsic phenotypic features of individual cells in a short video. By clustering these features with a simple machine learning algorithm, we can differentiate Escherichia coli from similar-sized polystyrene beads, distinguish bacteria with different shapes, and distinguish E. coli from urine particles. We applied the method to detect urinary tract infections in 104 patient urine samples with a 30 s LVSi video, and the results showed 92.3% accuracy compared with the clinical culture results. This technology provides opportunities for rapid bacterial infection diagnosis at POC settings.

High-Throughput Screening Identifies Synthetic Peptides with Antibacterial Activity against Mycobacterium abscessus and Serum Stability

The rise in antibiotic resistance in bacteria has spawned new technological approaches for identifying novel antimicrobials with narrow specificity. Current antibiotic treatment regimens and antituberculosis drugs are not effective in treating Mycobacterium abscessus. Meanwhile, antimicrobial peptides are gaining prominence as alternative antimicrobials due to their specificity toward anionic bacterial membranes, rapid action, and limited development of resistance. To rapidly identify antimicrobial peptide candidates, our group has developed a high-density peptide microarray consisting of 125,000 random synthetic peptides screened for interaction with the mycobacterial cell surface of M. abscessus morphotypes. From the array screening, peptides positive for interaction were synthesized and their antimicrobial activity was validated. Overall, six peptides inhibited the M. abscessus smooth morphotype (IC₅₀ = 1.7 μM for all peptides) and had reduced activity against the M. abscessus rough morphotype (IC₅₀ range: 13-82 μM). Peptides ASU2056 and ASU2060 had minimum inhibitory concentration values of 32 and 8 μM, respectively, against the M. abscessus smooth morphotype. Additionally, ASU2060 (8 μM) was active against Escherichia coli, including multidrug-resistant E. coli clinical isolates, Pseudomonas aeruginosa, and methicillin-resistant Staphylococcus aureus. ASU2056 and ASU2060 exhibited no significant hemolytic activity at biologically relevant concentrations, further supporting these peptides as promising therapeutic candidates. Moreover, ASU2060 retained antibacterial activity after preincubation in human serum for 24 h. With antimicrobial resistance on the rise, methods such as those presented here will streamline the peptide discovery process for targeted antimicrobial peptides.

A Cascaded Droplet Microfluidic Platform Enables High-Throughput Single Cell Antibiotic Susceptibility Testing at Scale

The global threat of antibiotic resistance underscores critical but unmet needs for rapid antibiotic susceptibility testing (AST) technologies. To this end, droplet microfluidic-based single-cell AST offers promise by achieving unprecedented rapidity, but its potential for clinical use is marred by the capacity of testing one to few antibiotic conditions per device, which falls short from the required scale in clinically relevant scenarios. To lift the scalability constraint in rapid single-cell AST technologies, a new cascaded droplet microfluidic platform that can streamline bacteria/antibiotic mixing, single-cell encapsulation within picoliter droplets, incubation, and detection in a continuous, assembly-line-like workflow is developed. The scalability of the platform is demonstrated by generating 32 groups of ≈10 000 droplets with custom antibiotic conditions within a single device, from which a new statistics-based method is used to analyze the single cell data and produce clinically useful antibiograms with minimum inhibitory concentrations in ≈90 min for the first antibiotic, plus 2 min for each subsequent antibiotic condition. Potential clinical utility of this platform is demonstrated by testing three clinical isolates and eight urine specimens against four frequently used antibiotics, and 100% and 93.8% categorical agreements are achieved compared to laboratory-based results that became available after 48 h.

Rapid Antimicrobial Susceptibility Testing on Clinical Urine Samples by Video-Based Object Scattering Intensity Detection

To combat the ongoing public health threat of antibiotic-resistant infections, a technology that can quickly identify infecting bacterial pathogens and concurrently perform antimicrobial susceptibility testing (AST) in point-of-care settings is needed. Here, we develop a technology for point-of-care AST with a low-magnification solution scattering imaging system and a real-time video-based object scattering intensity detection method. The low magnification (1-2×) optics provides sufficient volume for direct imaging of bacteria in urine samples, avoiding the time-consuming process of culture-based bacterial isolation and enrichment. Scattering intensity from moving bacteria and particles in the sample is obtained by subtracting both spatial and temporal background from a short video. The time profile of scattering intensity is correlated with the bacterial growth rate and bacterial response to antibiotic exposure. Compared to the image-based bacterial tracking and counting method we previously developed, this simple image processing algorithm accommodates a wider range of bacterial concentrations, simplifies sample preparation, and greatly reduces the computational cost of signal processing. Furthermore, development of this simplified processing algorithm eases implementation of multiplexed detection and allows real-time signal readout, which are essential for point-of-care AST applications. To establish the method, 130 clinical urine samples were tested, and the results demonstrated an accuracy of ∼92% within 60-90 min for UTI diagnosis. Rapid AST of 55 positive clinical samples revealed 98% categorical agreement with both the clinical culture results and the on-site parallel AST validation results. This technology provides opportunities for prompt infection diagnosis and accurate antibiotic prescriptions in point-of-care settings.

Nanomotion Detection-Based Rapid Antibiotic Susceptibility Testing

Rapid antibiotic susceptibility testing (AST) could play a major role in fighting multidrug-resistant bacteria. Recently, it was discovered that all living organisms oscillate in the range of nanometers and that these oscillations, referred to as nanomotion, stop as soon the organism dies. This finding led to the development of rapid AST techniques based on the monitoring of these oscillations upon exposure to antibiotics. In this review, we explain the working principle of this novel technique, compare the method with current ASTs, explore its application and give some advice about its implementation. As an illustrative example, we present the application of the technique to the slowly growing and pathogenic Bordetella pertussis bacteria.

Direct microfluidic antibiotic resistance testing in urine with smartphone capture: significant variation in sample matrix interference between individual human urine samples

Direct antibiotic susceptibility tests for urinary tract infections should be assessed using a wide range of individual urine samples to identify matrix interference.