Nanomotion Detection Method for Testing Antibiotic Resistance and Susceptibility of Slow-Growing Bacteria

Culture-free detection of β-lactamase-Producing bacteria in urinary tract infections using a paper sensor

Developing simple, inexpensive, fast, sensitive, and specific probes for antibiotic-resistant bacteria is crucial for the management of urinary tract infections (UTIs). We here propose a paper-based sensor for the rapid detection of β-lactamase-producing bacteria in the urine samples of UTI patients. By conjugating a strongly electronegative group -N+(CH3)3 with the core structures of cephalosporin and carbapenem antibiotics, two visual probes were achieved to respectively target the extended-spectrum/AmpC β-lactamases (ESBL/AmpC) and carbapenemase, the two most prevalent factors causing antibiotic resistance. By integrating these probes into a portable paper sensor, we confirmed 10 and 8 cases out of 30 clinical urine samples as ESBL/AmpC- and carbapenemase-positive, respectively, demonstrating 100% clinical sensitivity and specificity. This paper sensor can be easily conducted on-site, without resorting to bacterial culture, providing a solution to the challenge of rapid detection of β-lactamase-producing bacteria, particularly in resource-limited settings.

Accurate and rapid antibiotic susceptibility testing using a machine learning-assisted nanomotion technology platform

Antimicrobial resistance (AMR) is a major public health threat, reducing treatment options for infected patients. AMR is promoted by a lack of access to rapid antibiotic susceptibility tests (ASTs). Accelerated ASTs can identify effective antibiotics for treatment in a timely and informed manner. We describe a rapid growth-independent phenotypic AST that uses a nanomotion technology platform to measure bacterial vibrations. Machine learning techniques are applied to analyze a large dataset encompassing 2762 individual nanomotion recordings from 1180 spiked positive blood culture samples covering 364 Escherichia coli and Klebsiella pneumoniae isolates exposed to cephalosporins and fluoroquinolones. The training performances of the different classification models achieve between 90.5 and 100% accuracy. Independent testing of the AST on 223 strains, including in clinical setting, correctly predict susceptibility and resistance with accuracies between 89.5% and 98.9%. The study shows the potential of this nanomotion platform for future bacterial phenotype delineation.

Machine learning method for the classification of the state of living organisms' oscillations

The World Health Organization highlights the urgent need to address the global threat posed by antibiotic-resistant bacteria. Efficient and rapid detection of bacterial response to antibiotics and their virulence state is crucial for the effective treatment of bacterial infections. However, current methods for investigating bacterial antibiotic response and metabolic state are time-consuming and lack accuracy. To address these limitations, we propose a novel method for classifying bacterial virulence based on statistical analysis of nanomotion recordings. We demonstrated the method by classifying living Bordetella pertussis bacteria in the virulent or avirulence phase, and dead bacteria, based on their cellular nanomotion signal. Our method offers significant advantages over current approaches, as it is faster and more accurate. Additionally, its versatility allows for the analysis of cellular nanomotion in various applications beyond bacterial virulence classification.

Nanomotion technology in combination with machine learning: a new approach for a rapid antibiotic susceptibility test for Mycobacterium tuberculosis

Nanomotion technology is a growth-independent approach that can be used to detect and record the vibrations of bacteria attached to cantilevers. We have developed a nanomotion-based antibiotic susceptibility test (AST) protocol for Mycobacterium tuberculosis (MTB). The protocol was used to predict strain phenotype towards isoniazid (INH) and rifampicin (RIF) using a leave-one-out cross-validation (LOOCV) and machine learning techniques. This MTB-nanomotion protocol takes 21 h, including cell suspension preparation, optimized bacterial attachment to functionalized cantilever, and nanomotion recording before and after antibiotic exposure. We applied this protocol to MTB isolates (n = 40) and were able to discriminate between susceptible and resistant strains for INH and RIF with a maximum sensitivity of 97.4% and 100%, respectively, and a maximum specificity of 100% for both antibiotics when considering each nanomotion recording to be a distinct experiment. Grouping recordings as triplicates based on source isolate improved sensitivity and specificity to 100% for both antibiotics. Nanomotion technology can potentially reduce time-to-result significantly compared to the days and weeks currently needed for current phenotypic ASTs for MTB. It can further be extended to other anti-TB drugs to help guide more effective TB treatment.

Activated alkyne-enabled turn-on click bioconjugation with cascade signal amplification for ultrafast and high-throughput antibiotic screening

Antimicrobial susceptibility testing plays a pivotal role in the discovery of new antibiotics. However, the development of simple, sensitive, and rapid assessment approaches remains challenging. Herein, we report an activated alkyne-based cascade signal amplification strategy for ultrafast and high-throughput antibiotic screening. First of all, a novel water-soluble aggregation-induced emission (AIE) luminogen is synthesized, which contains an activated alkyne group to enable fluorescence turn-on and metal-free click bioconjugation under physiological conditions. Taking advantage of the in-house established method for bacterial lysis, a number of clickable biological substances (i.e., bacterial solutes and debris) are released from the bacterial bodies, which remarkably increases the quantity of analytes. By means of the activated alkyne-mediated turn-on click bioconjugation, the system fluorescence signal is significantly amplified due to the increased labeling sites as well as the AIE effect. Such a cascade signal amplification strategy efficiently improves the detection sensitivity and thus enables ultrafast antimicrobial susceptibility assessment. By integration with a microplate reader, this approach is further applied to high-throughput antibiotic screening.

Fiber-integrated cantilever-based nanomechanical biosensors as a tool for rapid antibiotic susceptibility testing

There is an urgent need for developing rapid and affordable antibiotic susceptibility testing (AST) technologies to inhibit the overuse of antibiotics. In this study, a novel microcantilever nanomechanical biosensor based on Fabry-Pérot interference demodulation was developed for AST. To construct the biosensor, a cantilever was integrated with the single mode fiber in order to form the Fabry-Pérot interferometer (FPI). After the attachment of bacteria on the cantilever, the fluctuations of cantilever caused by the bacterial movements were detected by monitoring the changes of resonance wavelength in the interference spectrum. We applied this methodology to Escherichia coli and Staphylococcus aureus, showing the amplitude of cantilever's fluctuations was positively related on the quantity of bacteria immobilized on the cantilever and associated with the bacterial metabolism. The response of bacteria to antibiotics was dependent on the types of bacteria, the types and concentrations of antibiotics. Moreover, the minimum inhibitory and bactericidal concentrations for Escherichia coli were obtained within 30 minutes, demonstrating the capacity of this method for rapid AST. Benefiting from the simplicity and portability of the optical fiber FPI-based nanomotion detection device, the developed nanomechanical biosensor in this study provides a promising technique for AST and a more rapid alternative for clinical laboratories.

Differences in bacteria nanomotion profiles and neutrophil nanomotion during phagocytosis

The main goal of this work is to highlight the connection between nanomotion and the metabolic activity of living cells. We therefore monitored the nanomotion of four different clinical strains of bacteria (prokaryotes) and the bacterial phagocytosis by neutrophil granulocytes (eukaryotes). All clinical strains of bacteria, regardless of their biochemical profile, showed pronounced fluctuations. Importantly, the nature of their nanomotions was different for the different strains. Flagellated bacteria (Escherichia coli, Proteus mirabilis) showed more pronounced movements than the non-flagellated forms (Staphylococcus aureus, Klebsiella pneumoniae). The unprimed neutrophil did not cause any difference in cantilever oscillations with control. However, in the process of phagocytosis of S. aureus (metabolically active state), a significant activation of neutrophil granulocytes was observed and cell nanomotions were maintained at a high level for up to 30 min of observation. These preliminary results indicate that nanomotion seems to be specific to different bacterial species and could be used to monitor, in a label free manner, basic cellular processes.

Mitochondrial nanomotion measured by optical microscopy

Nanometric scale size oscillations seem to be a fundamental feature of all living organisms on Earth. Their detection usually requires complex and very sensitive devices. However, some recent studies demonstrated that very simple optical microscopes and dedicated image processing software can also fulfill this task. This novel technique, termed as optical nanomotion detection (ONMD), was recently successfully used on yeast cells to conduct rapid antifungal sensitivity tests. In this study, we demonstrate that the ONMD method can monitor motile sub-cellular organelles, such as mitochondria. Here, mitochondrial isolates (from HEK 293 T and Jurkat cells) undergo predictable motility when viewed by ONMD and triggered by mitochondrial toxins, citric acid intermediates, and dietary and bacterial fermentation products (short-chain fatty acids) at various doses and durations. The technique has superior advantages compared to classical methods since it is rapid, possesses a single organelle sensitivity, and is label- and attachment-free.

Programmable molecular circuit discriminates multidrug-resistant bacteria

Recognizing multidrug-resistant (MDR) bacteria with high accuracy and precision from clinical samples has long been a difficulty. For reliable detection of MDR bacteria, we investigated a programmable molecular circuit called the Background-free isothermal circuital kit (BRICK). The BRICK method provides a near-zero background signal by integrating four inherent modules equivalent to the conversion, amplification, separation, and reading modules. Interference elimination is largely owing to a molybdenum disulfide nanosheets-based fluorescence nanoswitch and non-specific suppression mediated by molecular inhibitors. In less than 70 ​min, an accurate distinction of various MDR bacteria was achieved without bacterial lysis. The BRICK technique detected 6.73 ​CFU/mL of methicillin-resistant Staphylococcus aureus in clinical samples in a proof-of-concept trial. By simply reprogramming the sequence panel, such a high signal-to-noise characteristic has been proven in the four other superbugs. The proposed BRICK method can provide a universal platform for infection surveillance and environmental management thanks to its superior programmability.

Rapid Bacteria Detection from Patients' Blood Bypassing Classical Bacterial Culturing

Sepsis is a life-threatening condition mostly caused by a bacterial infection resulting in inflammatory reaction and organ dysfunction if not treated effectively. Rapid identification of the causing bacterial pathogen already in the early stage of bacteremia is therefore vital. Current technologies still rely on time-consuming procedures including bacterial culturing up to 72 h. Our approach is based on ultra-rapid and highly sensitive nanomechanical sensor arrays. In measurements we observe two clearly distinguishable distributions consisting of samples with bacteria and without bacteria respectively. Compressive surface stress indicates the presence of bacteria. For this proof-of-concept, we extracted total RNA from EDTA whole blood samples from patients with blood-culture-confirmed bacteremia, which is the reference standard in diagnostics. We determined the presence or absence of bacterial RNA in the sample through 16S-rRNA hybridization and species-specific probes using nanomechanical sensor arrays. Via both probes, we identified two clinically highly-relevant bacterial species i.e., Escherichia coli and Staphylococcus aureus down to an equivalent of 20 CFU per milliliter EDTA whole blood. The dynamic range of three orders of magnitude covers most clinical cases. We correctly identified all patient samples regarding the presence or absence of bacteria. We envision our technology as an important contribution to early and sensitive sepsis diagnosis directly from blood without requirement for cultivation. This would be a game changer in diagnostics, as no commercial PCR or POCT device currently exists who can do this.

Living Sample Viability Measurement Methods from Traditional Assays to Nanomotion

Living sample viability measurement is an extremely common process in medical, pharmaceutical, and biological fields, especially drug pharmacology and toxicology detection. Nowadays, there are a number of chemical, optical, and mechanical methods that have been developed in response to the growing demand for simple, rapid, accurate, and reliable real-time living sample viability assessment. In parallel, the development trend of viability measurement methods (VMMs) has increasingly shifted from traditional assays towards the innovative atomic force microscope (AFM) oscillating sensor method (referred to as nanomotion), which takes advantage of the adhesion of living samples to an oscillating surface. Herein, we provide a comprehensive review of the common VMMs, laying emphasis on their benefits and drawbacks, as well as evaluating the potential utility of VMMs. In addition, we discuss the nanomotion technique, focusing on its applications, sample attachment protocols, and result display methods. Furthermore, the challenges and future perspectives on nanomotion are commented on, mainly emphasizing scientific restrictions and development orientations.

Nanotechnology Approaches for Rapid Detection and Theranostics of Antimicrobial Resistant Bacterial Infections

As declared by WHO, antimicrobial resistance (AMR) is a high priority issue with a pressing need to develop impactful technologies to curb it. The rampant and inappropriate use of antibiotics due to the lack of adequate and timely diagnosis is a leading cause behind AMR evolution. Unfortunately, populations with poor economic status and those residing in densely populated areas are the most affected ones, frequently leading to emergence of AMR pathogens. Classical approaches for AMR diagnostics like phenotypic methods, biochemical assays, and molecular techniques are cumbersome and resource-intensive and involve a long turnaround time to yield confirmatory results. In contrast, recent emergence of nanotechnology-assisted approaches helps to overcome challenges in classical approaches and offer simpler, more sensitive, faster, and more affordable solutions for AMR diagnostics. Nanomaterial platforms (metallic, quantum-dot, carbon-based, upconversion, etc.), nanoparticle-based rapid point-of-care platforms, nano-biosensors (optical, mechanical, electrochemical), microfluidic-assisted devices, and importantly, nanotheranostic devices for diagnostics with treatment of AMR infections are examples of rapidly growing nanotechnology approaches used for AMR management. This review comprehensively summarizes the past 10 years of research progress on nanotechnology approaches for AMR diagnostics and for estimating antimicrobial susceptibility against commonly used antibiotics. This review also highlights several bottlenecks in nanotechnology approaches that need to be addressed prior to considering their translation to clinics.

The Dynamics of Single-Cell Nanomotion Behaviour of Saccharomyces cerevisiae in a Microfluidic Chip for Rapid Antifungal Susceptibility Testing

The fast emergence of multi-resistant pathogenic yeasts is caused by the extensive—and sometimes unnecessary—use of broad-spectrum antimicrobial drugs. To rationalise the use of broad-spectrum antifungals, it is essential to have a rapid and sensitive system to identify the most appropriate drug. Here, we developed a microfluidic chip to apply the recently developed optical nanomotion detection (ONMD) method as a rapid antifungal susceptibility test. The microfluidic chip contains no-flow yeast imaging chambers in which the growth medium can be replaced by an antifungal solution without disturbing the nanomotion of the cells in the imaging chamber. This allows for recording the cellular nanomotion of the same cells at regular time intervals of a few minutes before and throughout the treatment with an antifungal. Hence, the real-time response of individual cells to a killing compound can be quantified. In this way, this killing rate provides a new measure to rapidly assess the susceptibility of a specific antifungal. It also permits the determination of the ratio of antifungal resistant versus sensitive cells in a population.

Direct Color Observation of Light-Driven Molecular Conformation-Induced Stress

Although usually complex to handle, nanomechanical sensors are exceptional, label-free tools for monitoring molecular conformational changes, which makes them of paramount importance in understanding biomolecular interactions. Herein, a simple and inexpensive mechanical imaging approach based on low-stiffness cantilevers with structural coloration (mechanochromic cantilevers (MMC)) is demonstrated, able to monitor and quantify molecular conformational changes with similar sensitivity to the classical optical beam detection method of cantilever-based sensors (≈4.6 × 10^-3  N m^-1 ). This high sensitivity is achieved by using a white light and an RGB camera working in the reflection configuration. The sensor performance is demonstrated by monitoring the UV-light induced reversible conformational changes of azobenzene molecules coating. The trans-cis isomerization of the azobenzene molecules induces a deflection of the cantilevers modifying their diffracted color, which returns to the initial state by cis-trans relaxation. Interestingly, the mechanical imaging enables a simultaneous 2D mapping of the response thus enhancing the spatial resolution of the measurements. A tight correlation is found between the color output and the cantilever's deflection and curvature angle (sensitivities of 5 × 10^-3  Hue µm^-1 and 1.5 × 10^-1  Hue (°)^-1 ). These findings highlight the suitability of low-stiffness MMC as an enabling technology for monitoring molecular changes with unprecedented simplicity, high-throughput capability, and functionalities.

Combating Antimicrobial Resistance via Single-Cell Diagnostic Technologies Powered by Droplet Microfluidics

Antimicrobial resistance is a global threat that if left unchecked could lead to 10 million annual mortalities by 2050. One factor contributing to the rise of multi-drug-resistant (MDR) pathogens is the reliance on traditional culture-based pathogen identification (ID) and antimicrobial susceptibility testing (AST) that typically takes several days. This delay of objective pathogen ID and AST information to inform clinical decision making results in clinicians treating patients empirically often using first-line, broad-spectrum antibiotics, contributing to the misuse/overuse of antibiotics. To combat the rise in MDR pathogens, there is a critical demand for rapid ID and AST technologies. Among the advances in ID and AST technologies in the past decade, single-cell diagnostic technologies powered by droplet microfluidics offer great promise due to their potential for high-sensitivity detection and rapid turnaround time. Our laboratory has been at the forefront of developing such technologies and applying them to diagnosing urinary tract infections (UTIs), one of the most common infections and a frequent reason for the prescription of antimicrobials. For pathogen ID, we first demonstrated the highly sensitive, amplification-free detection of single bacterial cells by confining them in picoliter-scale droplets and detection with fluorogenic peptide nucleic acid (PNA) probes that target their 16S rRNA (rRNA), a well-characterized marker for phylogenic classification. We subsequently improved the PNA probe design and enhanced detection sensitivity. For single-cell AST, we first employed a growth indicator dye and engineered an integrated device that allows us to detect growth from single bacterial cells under antibiotic exposure within 1 h, equivalent to two to three bacterial replications. To expand beyond testing a single antibiotic condition per device, a common limitation for droplet microfluidics, we developed an integrated programmable droplet microfluidic device for scalable single-cell AST. Using the scalable single-cell AST platform, we demonstrated the generation of up to 32 droplet groups in a single device with custom antibiotic titers and the capacity to scale up single-cell AST, and providing reliable pathogen categories beyond a binary call embodies a critical advance. Finally, we developed an integrated ID and AST platform. To this end, we developed a PNA probe panel that can identify nearly 90% of uropathogens and showed the quantitative detection of 16S rRNA from single bacterial cells in droplet-enabled AST after as little as 10 min of antibiotic exposure. This platform achieved both ID and AST from minimally processed urine samples in 30 min, representing one of the fastest turnaround times to date. In addition to tracing the development of our technologies, we compare them with contemporary research advances and offer our perspectives for future development, with the vision that single-cell ID and AST technologies powered by droplet microfluidics can indeed become a useful diagnostic tool for combating antimicrobial resistance.

Progressing Antimicrobial Resistance Sensing Technologies across Human, Animal, and Environmental Health Domains

The spread of antimicrobial resistance (AMR) is a rapidly growing threat to humankind on both regional and global scales. As countries worldwide prepare to embrace a One Health approach to AMR management, which is one that recognizes the interconnectivity between human, animal, and environmental health, increasing attention is being paid to identifying and monitoring key contributing factors and critical control points. Presently, AMR sensing technologies have significantly progressed phenotypic antimicrobial susceptibility testing (AST) and genotypic antimicrobial resistance gene (ARG) detection in human healthcare. For effective AMR management, an evolution of innovative sensing technologies is needed for tackling the unique challenges of interconnected AMR across various and different health domains. This review comprehensively discusses the modern state-of-play for innovative commercial and emerging AMR sensing technologies, including sequencing, microfluidic, and miniaturized point-of-need platforms. With a unique view toward the future of One Health, we also provide our perspectives and outlook on the constantly changing landscape of AMR sensing technologies beyond the human health domain.

Advances in Antimicrobial Resistance Monitoring Using Sensors and Biosensors: A Review

The indiscriminate use and mismanagement of antibiotics over the last eight decades have led to one of the main challenges humanity will have to face in the next twenty years in terms of public health and economy, i.e., antimicrobial resistance. One of the key approaches to tackling antimicrobial resistance is clinical, livestock, and environmental surveillance applying methods capable of effectively identifying antimicrobial non-susceptibility as well as genes that promote resistance. Current clinical laboratory practices involve conventional culture-based antibiotic susceptibility testing (AST) methods, taking over 24 h to find out which medication should be prescribed to treat the infection. Although there are techniques that provide rapid resistance detection, it is necessary to have new tools that are easy to operate, are robust, sensitive, specific, and inexpensive. Chemical sensors and biosensors are devices that could have the necessary characteristics for the rapid diagnosis of resistant microorganisms and could provide crucial information on the choice of antibiotic (or other antimicrobial medicines) to be administered. This review provides an overview on novel biosensing strategies for the phenotypic and genotypic determination of antimicrobial resistance and a perspective on the use of these tools in modern health-care and environmental surveillance.

Nanomechanical sensor for rapid and ultrasensitive detection of tumor markers in serum using nanobody

Early cancer diagnosis requires ultrasensitive detection of tumor markers in blood. To this end, we develop a novel microcantilever immunosensor using nanobodies (Nbs) as receptors. As the smallest antibody (Ab) entity comprising an intact antigen-binding site, Nbs achieve dense receptor layers and short distances between antigen-binding regions and sensor surfaces, which significantly elevate the generation and transmission of surface stress. Owing to the inherent thiol group at the C-terminus, Nbs are covalently immobilized on microcantilever surfaces in directed orientation via one-step reaction, which further enhances the stress generation. For microcantilever-based nanomechanical sensor, these advantages dramatically increase the sensor sensitivity. Thus, Nb-functionalized microcantilevers can detect picomolar concentrations of tumor markers with three orders of magnitude higher sensitivity, when compared with conventional Ab-functionalized microcantilevers. This proof-of-concept study demonstrates an ultrasensitive, label-free, rapid, and low-cost method for tumor marker detection. Moreover, interestingly, we find Nb inactivation on sensor interfaces when using macromolecule blocking reagents. The adsorption-induced inactivation is presumably caused by the change of interfacial properties, due to binding site occlusion upon complex coimmobilization formations. Our findings are generalized to any coimmobilization methodology for Nbs and, thus, for the construction of high-performance immuno-surfaces.

ELECTRONIC SUPPLEMENTARY MATERIAL

Supplementary material (experimental section, HER2 detection using anti-HER2-mAb-functionalized microcantilevers) is available in the online version of this article at 10.1007/s12274-021-3588-4.

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.

Droplet-Based Single-Cell Measurements of 16S rRNA Enable Integrated Bacteria Identification and Pheno-Molecular Antimicrobial Susceptibility Testing from Clinical Samples in 30 min

Empiric broad-spectrum antimicrobial treatments of urinary tract infections (UTIs) have contributed to widespread antimicrobial resistance. Clinical adoption of evidence-based treatments necessitates rapid diagnostic methods for pathogen identification (ID) and antimicrobial susceptibility testing (AST) with minimal sample preparation. In response, a microfluidic droplet-based platform is developed for achieving both ID and AST from urine samples within 30 min. In this platform, fluorogenic hybridization probes are utilized to detect 16S rRNA from single bacterial cells encapsulated in picoliter droplets, enabling molecular identification of uropathogenic bacteria directly from urine in as little as 16 min. Moreover, in-droplet single-bacterial measurements of 16S rRNA provide a surrogate for AST, shortening the exposure time to 10 min for gentamicin and ciprofloxacin. A fully integrated device and screening workflow were developed to test urine specimens for one of seven unique diagnostic outcomes including the presence/absence of Gram-negative bacteria, molecular ID of the bacteriaas Escherichia coli, an Enterobacterales, or other organism, and assessment of bacterial susceptibility to ciprofloxacin. In a 50-specimen clinical comparison study, the platform demonstrates excellent performance compared to clinical standard methods (areas-under-curves, AUCs >0.95), within a small fraction of the turnaround time, highlighting its clinical utility.

Dynamic Laser Speckle Imaging Meets Machine Learning to Enable Rapid Antibacterial Susceptibility Testing (DyRAST)

Rapid antibacterial susceptibility testing (RAST) methods are of significant importance in healthcare, as they can assist caregivers in timely administration of the correct treatments. Various RAST techniques have been reported for tracking bacterial phenotypes, including size, shape, motion, and redox state. However, they still require bulky and expensive instruments-which hinder their application in resource-limited environments-and/or utilize labeling reagents which can interfere with antibiotics and add to the total cost. Furthermore, the existing RAST methods do not address the potential gradual adaptation of bacteria to antibiotics, which can lead to a false diagnosis. In this work, we present a RAST approach by leveraging machine learning to analyze time-resolved dynamic laser speckle imaging (DLSI) results. DLSI captures the change in bacterial motion in response to antibiotic treatments. Our method accurately predicts the minimum inhibitory concentration (MIC) of ampicillin and gentamicin for a model strain of Escherichia coli (E. coli K-12) in 60 min, compared to 6 h using the currently FDA-approved phenotype-based RAST technique. In addition to ampicillin (a β-lactam) and gentamicin (an aminoglycoside), we studied the effect of ceftriaxone (a third-generation cephalosporin) on E. coli K-12. The machine learning algorithm was trained and validated using the overnight results of a gold standard antibacterial susceptibility testing method enabling prediction of MIC with a similarly high accuracy yet substantially faster.

Cantilever Sensors for Rapid Optical Antimicrobial Sensitivity Testing

Growing antimicrobial resistance (AMR) is a serious global threat to human health. Current methods to detect resistance include phenotypic antibiotic sensitivity testing (AST), which measures bacterial growth and is therefore hampered by a slow time to obtain results (∼12–24 h). Therefore, new rapid phenotypic methods for AST are urgently needed. Nanomechanical cantilever sensors have recently shown promise for rapid AST but challenges of bacterial immobilization can lead to variable results. Herein, a novel cantilever-based method is described for detecting phenotypic antibiotic resistance within ∼45 min, capable of detecting single bacteria. This method does not require complex, variable bacterial immobilization and instead uses a laser and detector system to detect single bacterial cells in media as they pass through the laser focus. This provides a simple readout of bacterial antibiotic resistance by detecting growth (resistant) or death (sensitive), much faster than the current methods. The potential of this technique is demonstrated by determining the resistance in both laboratory and clinical strains of Escherichia coli (E. coli), a key species responsible for clinically burdensome urinary tract infections. This work provides the basis for a simple and fast diagnostic tool to detect antibiotic resistance in bacteria, reducing the health and economic burdens of AMR.

Single yeast cell nanomotions correlate with cellular activity

Living single yeast cells show a specific cellular motion at the nanometer scale with a magnitude that is proportional to the cellular activity of the cell. We characterized this cellular nanomotion pattern of nonattached single yeast cells using classical optical microscopy. The distribution of the cellular displacements over a short time period is distinct from random motion. The range and shape of such nanomotion displacement distributions change substantially according to the metabolic state of the cell. The analysis of the nanomotion frequency pattern demonstrated that single living yeast cells oscillate at relatively low frequencies of around 2 hertz. The simplicity of the technique should open the way to numerous applications among which antifungal susceptibility tests seem the most straightforward.

A perspective view on the nanomotion detection of living organisms and its features

The insurgence of newly arising, rapidly developing health threats, such as drug-resistant bacteria and cancers, is one of the most urgent public-health issues of modern times. This menace calls for the development of sensitive and reliable diagnostic tools to monitor the response of single cells to chemical or pharmaceutical stimuli. Recently, it has been demonstrated that all living organisms oscillate at a nanometric scale and that these oscillations stop as soon as the organisms die. These nanometric scale oscillations can be detected by depositing living cells onto a micro-fabricated cantilever and by monitoring its displacements with an atomic force microscope-based electronics. Such devices, named nanomotion sensors, have been employed to determine the resistance profiles of life-threatening bacteria within minutes, to evaluate, among others, the effect of chemicals on yeast, neurons, and cancer cells. The data obtained so far demonstrate the advantages of nanomotion sensing devices in rapidly characterizing microorganism susceptibility to pharmaceutical agents. Here, we review the key aspects of this technique, presenting its major applications. and detailing its working protocols.

Yeast Nanometric Scale Oscillations Highlights Fibronectin Induced Changes in C. albicans

Yeast resistance to antifungal drugs is a major public health issue. Fungal adhesion onto the host mucosal surface is still a partially unknown phenomenon that is modulated by several actors among which fibronectin plays an important role. Targeting the yeast adhesion onto the mucosal surface could lead to potentially highly efficient treatments. In this work, we explored the effect of fibronectin on the nanomotion pattern of different Candida albicans strains by atomic force microscopy (AFM)-based nanomotion detection and correlated the cellular oscillations to the yeast adhesion onto epithelial cells. Preliminary results demonstrate that strongly adhering strains reduce their nanomotion activity upon fibronectin exposure whereas low adhering Candida remain unaffected. These results open novel avenues to explore cellular reactions upon exposure to stimulating agents and possibly to monitor in a rapid and simple manner adhesive properties of C. albicans.

A Rapid Unraveling of the Activity and Antibiotic Susceptibility of Mycobacteria

The development of antibiotic-resistant bacteria is a worldwide health-related emergency that calls for new tools to study the bacterial metabolism and to obtain fast diagnoses. Indeed, the conventional analysis time scale is too long and affects our ability to fight infections. Slowly growing bacteria represent a bigger challenge, since their analysis may require up to months. Among these bacteria, Mycobacterium tuberculosis, the causative agent of tuberculosis, has caused more than 10 million new cases and 1.7 million deaths in 2016 only. We employed a particularly powerful nanomechanical oscillator, the nanomotion sensor, to characterize rapidly and in real time tuberculous and nontuberculous bacterial species, Mycobacterium bovis bacillus Calmette-Guérin and Mycobacterium abscessus, respectively, exposed to different antibiotics. Here, we show how high-speed and high-sensitivity detectors, the nanomotion sensors, can provide a rapid and reliable analysis of different mycobacterial species, obtaining qualitative and quantitative information on their responses to different drugs. This is the first application of the technique to tackle the urgent medical issue of mycobacterial infections, evaluating the dynamic response of bacteria to different antimicrobial families and the role of the replication rate in the resulting nanomotion pattern. In addition to a fast analysis, which could massively benefit patients and the overall health care system, we investigated the real-time responses of the bacteria to extract unique information on the bacterial mechanisms triggered in response to antibacterial pressure, with consequences both at the clinical level and at the microbiological level.

Recent Advances in the Race to Design a Rapid Diagnostic Test for Antimicrobial Resistance

Even with advances in antibiotic therapies, bacterial infections persistently plague society and have amounted to one of the most prevalent issues in healthcare today. Moreover, the improper and excessive administration of antibiotics has led to resistance of many pathogens to prescribed therapies, rendering such antibiotics ineffective against infections. While the identification and detection of bacteria in a patient's sample is critical for point-of-care diagnostics and in a clinical setting, the consequent determination of the correct antibiotic for a patient-tailored therapy is equally crucial. As a result, many recent research efforts have been focused on the development of sensors and systems that correctly guide a physician to the best antibiotic to prescribe for an infection, which can in turn, significantly reduce the instances of antibiotic resistance and the evolution of bacteria "superbugs." This review details the advantages and shortcomings of the recent advances (focusing from 2016 and onward) made in the developments of antimicrobial susceptibility testing (AST) measurements. Detection of antibiotic resistance by genomic AST techniques relies on the prediction of antibiotic resistance via extracted bacterial DNA content, while phenotypic determinations typically track physiological changes in cells and/or populations exposed to antibiotics. Regardless of the method used for AST, factors such as cost, scalability, and assay time need to be weighed into their design. With all of the expansive innovation in the field, which technology and sensing systems demonstrate the potential to detect antimicrobial resistance in a clinical setting?