Antifungal Susceptibility Testing of Aspergillus niger on Silicon Microwells by Intensity-Based Reflectometric Interference Spectroscopy

Photonic Si microwell architectures for rapid antifungal susceptibility determination of Candida auris

We present the application of a photonic silicon chip-based optical sensor system for expeditious and phenotypic antifungal susceptibility testing. This label-free diagnostic assay optically monitors the growth of Candida auris at varying antifungal concentrations on a microwell-structured silicon chip in real-time, and antifungal susceptibility is detected within 6 h, four times faster than in the current gold standard method.

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.

Optical biosensors for environmental monitoring: Recent advances and future perspectives in bacterial detection

The environmental contamination due to bacterial proliferation vs their identification is the major deciding factor in the spread of diseases leading to pandemics. The advent of drug-resistant pathogenic contaminants in our environment has further added to the load of complications associated with their diagnosis and treatment. Obstructing the spread of such infections, prioritizes the expansion of sensor-based diagnostics, effectuating, a sturdy detection of disease-causing microbes, contaminating our surroundings in shortest possible time, with minimal expenditure. Among many sensors known, optical biosensors promote the recognition of pathogens befouling the environment through a comparatively intuitive, brisk, portable, multitudinous, and thrifty approach. This article reviews the recent progresses in optical biosensor-based systems for effective environmental monitoring. The technical and methodological perspectives of fundamental optical-sensing platforms are reviewed, combined with the pros and cons of every procedure. Eventually, the obstacles lying in the path of development of an effective optical biosensor device for bio-monitoring and its future perspectives are highlighted in the present work.

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.

Theoretical optimization of a frequency-domain- based color polarization interference sensor via coupling with a Gaussian beam

In this paper, a Gaussian-beam-coupled color polarization interference (CCPI) sensor with an adjustable digital Gaussian filter was proposed theoretically in the frequency domain. The coupling principle of a traditional color polarization interference (CPI) sensor and a Gaussian beam was investigated, and sensitivity optimization was then implemented. The formation of a doublet is related to the shape of a CPI curve, expected wavelength, and FWHM of the Gaussian beam. Based on the calculated results, the angle between the two polarizers and the obliquity of the wave plate are the two most significant adjusting parameters. The sensitivity of a CCPI sensor is approximately twofold higher than that of a traditional CPI sensor. The sensing range is also related to the FWHM of the Gaussian beam and a larger FWHM usually means a wider sensing range. We also found that the sensitivity would reach a maximum when the incident angle is near the total internal reflection angle. Besides, a longer incident wavelength usually corresponds to a higher sensitivity and the sensitivity could reach as high as 9270 nm/refractive index unit when the resonance wavelength is 977.40 nm.

A 3D-printed microfluidic gradient generator with integrated photonic silicon sensors for rapid antimicrobial susceptibility testing

With antimicrobial resistance becoming a major threat to healthcare settings around the world, there is a paramount need for rapid point-of-care antimicrobial susceptibility testing (AST) diagnostics. Unfortunately, most currently available clinical AST tools are lengthy, laborious, or are simply inappropriate for point-of-care testing. Herein, we design a 3D-printed microfluidic gradient generator that automatically produces two-fold dilution series of clinically relevant antimicrobials. We first establish the compatibility of these generators for classical AST (i.e., broth microdilution) and then extend their application to include a complete on-chip label-free and phenotypic AST. This is accomplished by the integration of photonic silicon chips, which provide a preferential surface for microbial colonization and allow optical tracking of bacterial behavior and growth at a solid-liquid interface in real-time by phase shift reflectometric interference spectroscopic measurements (PRISM). Using Escherichia coli and ciprofloxacin as a model pathogen-drug combination, we successfully determine the minimum inhibitory concentration within less than 90 minutes. This gradient generator-based PRISM assay provides an integrated AST device that is viable for convenient point-of-care testing and offers a promising and most importantly, rapid alternative to current clinical practices, which extend to 8-24 h.

Shining light in blind alleys: deciphering bacterial attachment in silicon microstructures

With new advances in infectious disease, antifouling surfaces, and environmental microbiology research comes the need to understand and control the accumulation and attachment of bacterial cells on a surface. Thus, we employ intrinsic phase-shift reflectometric interference spectroscopic measurements of silicon diffraction gratings to non-destructively observe the interactions between bacterial cells and abiotic, microstructured surfaces in a label-free and real-time manner. We conclude that the combination of specific material characteristics (i.e., substrate surface charge and topology) and characteristics of the bacterial cells (i.e., motility, cell charge, biofilm formation, and physiology) drive bacteria to adhere to a particular surface, often leading to a biofilm formation. Such knowledge can be exploited to predict antibiotic efficacy and biofilm formation, and enhance surface-based biosensor development, as well as the design of anti-biofouling strategies.

A method for high-throughput image-based antifungal screening

Robust antifungal screening is technically challenging particularly for filamentous fungi. We present a method for undertaking antifungal screening assays that builds upon existing broth dilution protocols and incorporates time resolved image-based assessment of fungal growth. We show that the method performs with different fungi, particularly those for which spores can be used as inoculum, and with different compound classes, can accurately assess susceptibility or otherwise in only few hours and can even account for differences in inherent growth properties of strains.