Surfactant-enhanced DNA accessibility to nuclease accelerates phenotypic β-lactam antibiotic susceptibility testing of Neisseria gonorrhoeae

YOLO Algorithm for Long-Term Tracking and Detection of Escherichia Coli at Different Depths of Microchannels Based on Microsphere Positioning Assistance

The effect evaluation of the antibiotic susceptibility test based on bacterial solution is of great significance for clinical diagnosis and prevention of antibiotic abuse. Applying a microfluidic chip as the detection platform, the detection method of using microscopic images to observe bacteria under antibiotic can greatly speed up the detection time, which is more suitable for high-throughput detection. However, due to the influence of the depth of the microchannel, there are multiple layers of bacteria under the focal depth of the microscope, which greatly affects the counting and recognition accuracy and increases the difficulty of relocation of the target bacteria, as well as extracting the characteristics of bacterial liquid changes under the action of antibiotics. After the focal depth of the target bacteria is determined, although the z-axis can be controlled with the help of a three-dimensional micro-operator, the equipment is difficult to operate and the long-term changes of the target bacteria cannot be tracked quickly and accurately. In this paper, the YOLOv5 algorithm is adopted to accurately identify bacteria with different focusing states of multi-layer bacteria at the z-axis with any focal depth. In the meantime, a certain amount of microspheres were mixed into bacteria to assist in locating bacteria, which was convenient for tracking the growth state of bacteria over a long period, and the recognition rates of both bacteria and microspheres were high. The recognition accuracy and counting accuracy of bacteria are 0.734 and 0.714, and the two recognition rates of microspheres are 0.910 and 0.927, respectively, which are much higher than the counting accuracy of 0.142 for bacteria and 0.781 for microspheres with the method of enhanced depth of field (EDF method). Moreover, during long-term bacterial tracking and detection, target bacteria at multiple z-axis focal depth positions can be recorded by the aid of microspheres as a positioning aid for 3D reconstruction, and the focal depth positions can be repositioned within 3-10 h. The structural similarity (SSIM) of microscopic image structure differences at the same focal depth fluctuates between 0.960 and 0.975 at different times, and the root-mean-square error (RMSE) fluctuates between 8 and 12, which indicates that the method also has good relocation accuracy. Thus, this method provides the basis for rapid, high-throughput, and long-term analysis of microscopic changes (e.g., morphology, size) of bacteria detection under the addition of antibiotics with different concentrations based on microfluidic channels in the future.

Bridging the gap between development of point-of-care nucleic acid testing and patient care for sexually transmitted infections

The incidence rates of sexually transmitted infections (STIs), including the four major curable STIs - chlamydia, gonorrhea, trichomoniasis and, syphilis - continue to increase globally, causing medical cost burden and morbidity especially in low and middle-income countries (LMIC). There have seen significant advances in diagnostic testing, but commercial antigen-based point-of-care tests (POCTs) are often insufficiently sensitive and specific, while near-point-of-care (POC) instruments that can perform sensitive and specific nucleic acid amplification tests (NAATs) are technically complex and expensive, especially for LMIC. Thus, there remains a critical need for NAAT-based STI POCTs that can improve diagnosis and curb the ongoing epidemic. Unfortunately, the development of such POCTs has been challenging due to the gap between researchers developing new technologies and healthcare providers using these technologies. This review aims to bridge this gap. We first present a short introduction of the four major STIs, followed by a discussion on the current landscape of commercial near-POC instruments for the detection of these STIs. We present relevant research toward addressing the gaps in developing NAAT-based STI POCT technologies and supplement this discussion with technologies for HIV and other infectious diseases, which may be adapted for STIs. Additionally, as case studies, we highlight the developmental trajectory of two different POCT technologies, including one approved by the United States Food and Drug Administration (FDA). Finally, we offer our perspectives on future development of NAAT-based STI POCT technologies.

Leapfrogging laboratories: the promise and pitfalls of high-tech solutions for antimicrobial resistance surveillance in low-income settings

The scope and trajectory of today’s escalating antimicrobial resistance (AMR) crisis is inadequately captured by existing surveillance systems, particularly those of lower income settings. AMR surveillance systems typically collate data from routine culture and susceptibility testing performed in diagnostic bacteriology laboratories to support healthcare. Limited access to high quality culture and susceptibility testing results in the dearth of AMR surveillance data, typical of many parts of the world where the infectious disease burden and antimicrobial need are high. Culture and susceptibility testing by traditional techniques is also slow, which limits its value in infection management. Here, we outline hurdles to effective resistance surveillance in many low-income settings and encourage an open attitude towards new and evolving technologies that, if adopted, could close resistance surveillance gaps. Emerging advancements in point-of-care testing, laboratory detection of resistance through or without culture, and in data handling, have the potential to generate resistance data from previously unrepresented locales while simultaneously supporting healthcare. Among them are microfluidic, nucleic acid amplification technology and next-generation sequencing approaches. Other low tech or as yet unidentified innovations could also rapidly accelerate AMR surveillance. Parallel advances in data handling further promise to significantly improve AMR surveillance, and new frameworks that can capture, collate and use alternate data formats may need to be developed. We outline the promise and limitations of such technologies, their potential to leapfrog surveillance over currently available, conventional technologies in use today and early steps that health systems could take towards preparing to adopt them.

Machine Learning Establishes Single-Cell Calcium Dynamics as an Early Indicator of Antibiotic Response

Changes in bacterial physiology necessarily precede cell death in response to antibiotics. Herein we investigate the early disruption of Ca²⁺ homeostasis as a marker for antibiotic response. Using a machine learning framework, we quantify the temporal information encoded in single-cell Ca²⁺ dynamics. We find Ca²⁺ dynamics distinguish kanamycin sensitive and resistant cells before changes in gross cell phenotypes such as cell growth or protein stability. The onset time (pharmacokinetics) and probability (pharmacodynamics) of these aberrant Ca²⁺ dynamics are dose and time-dependent, even at the resolution of single-cells. Of the compounds profiled, we find Ca²⁺ dynamics are also an indicator of Polymyxin B activity. In Polymyxin B treated cells, we find aberrant Ca²⁺ dynamics precedes the entry of propidium iodide marking membrane permeabilization. Additionally, we find modifying membrane voltage and external Ca²⁺ concentration alters the time between these aberrant dynamics and membrane breakdown suggesting a previously unappreciated role of Ca²⁺ in the membrane destabilization during Polymyxin B treatment. In conclusion, leveraging live, single-cell, Ca²⁺ imaging coupled with machine learning, we have demonstrated the discriminative capacity of Ca²⁺ dynamics in identifying antibiotic-resistant bacteria.

Differential DNA accessibility to polymerase enables 30-minute phenotypic β-lactam antibiotic susceptibility testing of carbapenem-resistant Enterobacteriaceae

The rise in carbapenem-resistant Enterobacteriaceae (CRE) infections has created a global health emergency, underlining the critical need to develop faster diagnostics to treat swiftly and correctly. Although rapid pathogen-identification (ID) tests are being developed, gold-standard antibiotic susceptibility testing (AST) remains unacceptably slow (1-2 d), and innovative approaches for rapid phenotypic ASTs for CREs are urgently needed. Motivated by this need, in this manuscript we tested the hypothesis that upon treatment with β-lactam antibiotics, susceptible Enterobacteriaceae isolates would become sufficiently permeabilized, making some of their DNA accessible to added polymerase and primers. Further, we hypothesized that this accessible DNA would be detectable directly by isothermal amplification methods that do not fully lyse bacterial cells. We build on these results to develop the polymerase-accessibility AST (pol-aAST), a new phenotypic approach for β-lactams, the major antibiotic class for gram-negative infections. We test isolates of the 3 causative pathogens of CRE infections using ceftriaxone (CRO), ertapenem (ETP), and meropenem (MEM) and demonstrate agreement with gold-standard AST. Importantly, pol-aAST correctly categorized resistant isolates that are undetectable by current genotypic methods (negative for β-lactamase genes or lacking predictive genotypes). We also test contrived and clinical urine samples. We show that the pol-aAST can be performed in 30 min sample-to-answer using contrived urine samples and has the potential to be performed directly on clinical urine specimens.