A review of conventional detection and enumeration methods for pathogenic bacteria in food

Organic Electrochemical Transistors for Biomarker Detections

The improvement of living standards and the advancement of medical technology have led to an increased focus on health among individuals. Detections of biomarkers are feasible approaches to obtaining information about health status, disease progression, and response to treatment of an individual. In recent years, organic electrochemical transistors (OECTs) have demonstrated high electrical performances and effectiveness in detecting various types of biomarkers. This review provides an overview of the working principles of OECTs and their performance in detecting multiple types of biomarkers, with a focus on the recent advances and representative applications of OECTs in wearable and implantable biomarker detections, and provides a perspective for the future development of OECT-based biomarker sensors.

On-chip bioluminescence biosensor for the detection of microbial surface contamination

Detection of microbial pathogens is important for food safety reasons, and for monitoring sanitation in laboratory environments and health care settings. Traditional detection methods such as culture-based and nucleic acid-based methods are time-consuming, laborious, and require expensive laboratory equipment. Recently, ATP-based bioluminescence methods were developed to assess surface contamination, with commercial products available. In this study, we introduce a biosensor based on a CMOS image sensor for ATP-mediated chemiluminescence detection. The original lens and IR filter were removed from the CMOS sensor revealing a 12 MP periodic microlens/pixel array on an area of 6.5 mm × 3.6 mm. UltraSnap swabs are used to collect samples from solid surfaces including personal electronic devices, and office and laboratory equipment. Samples mixed with chemiluminescence reagents were placed directly on the surface of the image sensor. Close proximity of the sample to the photodiode array leads to high photon collection efficiency. The population of microorganisms can be assessed and quantified by analyzing the intensity of measured chemiluminescence. We report a linear range and limit of detection for measuring ATP in UltraSnap buffer of 10-1000 nM and 225 fmol, respectively. The performance of the CMOS-based device was compared to a commercial luminometer, and a high correlation with a Pearson's correlation coefficient of 0.98589 was obtained. The Bland-Altman plot showed no significant bias between the results of the two methods. Finally, microbial contamination of different surfaces was analyzed with both methods, and the CMOS biosensor exhibited the same trend as the commercial luminometer.

Rapid and ultra-sensitive lateral flow assay for pathogens based on multivalent aptamer and magnetic nanozyme

Ultra-sensitive LFA methods for pathogen detection commonly depended on tedious and time-consuming nucleic acid amplification. Here, a high affinity multivalent aptamer (multi-Apt) for S. aureus was obtained through exquisite engineering design. The scaffold and conformation of the multi-Apt were found to be key factors in the detection signal of aptsensors. After optimization, the binding affinity of the multi-Apt to S. aureus was improved by more than 8-fold from 135.9 nM to 16.77 nM. By the joint use of the multi-Apt and a multifunctional nanozyme Fe3O4@MOF@PtPd, a fast and ultra-sensitive LFA for S. aureus was developed (termed MA-MN LFA). In this method, a Fe3O4@MOF@PtPd nanozyme was modified with vancomycin and could efficiently capture and separate S. aureus. Moreover, the multi-Apt worked together with the nanozyme to bind with S. aureus to form a ternary complex at the same time, which simply the fabrication of LFA strip. The developed MA-MN LFA could detect S. aureus as low as 2 CFU/mL within 30 min and a wide linear range of 10-1 × 108 CFU/mL was obtained. The detection is easily operated, fast (can be completed within 30 min) and versatile for Gram-positive pathogens, thus has great potential as a powerful tool in pathogen detection.

Development and Application of Four Foodborne Pathogens by TaqMan Multiplex Real-Time PCR

A TaqMan multiplex real-time PCR (mRT-PCR) was developed to detect simultaneously Salmonella spp., Escherichia coli O157, Staphylococcus aureus, and Listeria monocytogenes in food samples. The method involves four sets of primers and probes tailored to the unique DNA sequences found in the invA, nuc, rfbE, and hly genes of each pathogen. The generated standard curves, correlating gene copy numbers with Ct values, demonstrated high accuracy (R2 > 0.99) and efficiency (92%-104%). Meanwhile, the limit of detection was 100 CFU/mL for the four target bacteria in artificially contaminated food samples after 6-8 h of enrichment. The assay's effectiveness was further verified by testing 80 naturally contaminated food samples, showing results largely in agreement with traditional culture methods. Overall, this newly developed TaqMan mRT-PCR, inclusive of a pre-enrichment step, proves to be a dependable and effective tool for detecting single or multiple pathogens in diverse food items, offering significant potential for in vitro diagnostics.

Siamese Networks for Clinically Relevant Bacteria Classification Based on Raman Spectroscopy

Identifying bacterial strains is essential in microbiology for various practical applications, such as disease diagnosis and quality monitoring of food and water. Classical machine learning algorithms have been utilized to identify bacteria based on their Raman spectra. However, convolutional neural networks (CNNs) offer higher classification accuracy, but they require extensive training sets and retraining of previous untrained class targets can be costly and time-consuming. Siamese networks have emerged as a promising solution. They are composed of two CNNs with the same structure and a final network that acts as a distance metric, converting the classification problem into a similarity problem. Classical machine learning approaches, shallow and deep CNNs, and two Siamese network variants were tailored and tested on Raman spectral datasets of bacteria. The methods were evaluated based on mean sensitivity, training time, prediction time, and the number of parameters. In this comparison, Siamese-model2 achieved the highest mean sensitivity of 83.61 ± 4.73 and demonstrated remarkable performance in handling unbalanced and limited data scenarios, achieving a prediction accuracy of 73%. Therefore, the choice of model depends on the specific trade-off between accuracy, (prediction/training) time, and resources for the particular application. Classical machine learning models and shallow CNN models may be more suitable if time and computational resources are a concern. Siamese networks are a good choice for small datasets and CNN for extensive data.

Unravelling the genomic secrets of bacterial fish pathogens: a roadmap to aquaculture sustainability

In the field of aquaculture, bacterial pathogens pose significant challenges to fish health and production. Advancements in genomic technologies have revolutionized our understanding of bacterial fish pathogens and their interactions with their host species. This review explores the application of genomic approaches in the identification, classification, and characterization of bacterial fish pathogens. Through an extensive analysis of the literature, we have compiled valuable data on 79 bacterial fish pathogens spanning 13 different phyla, encompassing their whole genome sequences. By leveraging high-throughput sequencing techniques, researchers have gained valuable insights into the genomic makeup of these pathogens, enabling a deeper understanding of their virulence factors and mechanisms of host interaction. Furthermore, genomic approaches have facilitated the discovery of potential vaccine and drug targets, opening up new avenues for the development of effective interventions against fish pathogens. Additionally, the utilization of genomics in fish disease resistance and control in aquaculture has shown promising results, enabling the identification of genetic markers associated with disease resistance traits. This review highlights the significant contributions of genomics to the field of fish pathogen research and underscores its potential for improving disease management strategies and enhancing the sustainability of aquaculture practices.

Sensitive Methods to Detect Single-Stranded Nucleic Acids of Food Pathogens Based on Cell-Free Protein Synthesis and Retroreflection Signal Detection

Cell-free protein synthesis (CFPS) has recently gained considerable attention as a new platform for developing methods to detect various molecules, ranging from small chemicals to biological macromolecules. Retroreflection has been used as an alternative signal to develop analytical methods because it can be detected by using a simple instrument comprising a white light source and a camera. Here, we report a novel reporter protein that couples the capability of CFPS and the simplicity of retroreflection signal detection. The design of the reporter was based on two pairs of protein-peptide interactions, SpyCatcher003-SpyTag003 and MDM2-PMI(N8A). MDM2-MDM2-SpyCatcher003 was decided as the reporter protein, and the two peptides, SpyTag003 and PMI(N8A), were immobilized on the surfaces of retroreflective Janus particles and microfluidic chips, respectively. The developed retroreflection signal detection system was combined with a previously reported CFPS reaction that can transduce the presence of a single-stranded nucleic acid into protein synthesis. The resulting methods were applied to detect 16S rRNAs of several foodborne pathogens. Concentration-dependent relationships were observed over a range of 10° fM to 102 pM, with the limits of detection being single-digit femtomolar concentrations. Considering the designability of the CFPS system for other targets, the retroreflection signal detection method will enable the development of novel methods to detect various molecules.

Directly Self-Assembly of Aligned Ag NWs Films at the Air-Water Interface for the Detection of Pathogens in Artificial Breath Aerosols

Exhaled aerosols from humans, containing various pathogens, are crucial for early disease diagnosis. However, the traditional pathogen detection methods, such as polymerase chain reaction, are often slow and cumbersome due to complex sampling and procedures. This study introduces a novel, direct, and label-free detection method for pathogens in respiratory aerosols, utilizing a highly aligned silver nanowire (Ag NW) film combined with a filter membrane (Ag NWs@filter) as a surface-enhanced Raman spectroscopy-active substrate. A large-scale, ordered silver nanowire film was developed through a simplified self-assembly process. This process eliminates the need for an organic phase and complex surface modifications of Ag NWs, which are common in other preparation methods. Subsequently, the fabricated Ag NWs@filter demonstrated its capability to continuously capture and efficiently preconcentrate pathogens from aerosols, achieving a remarkable detection limit of 3 × 103 CFU/mL, demonstrated using Escherichia coli (E. coli) as a model pathogen. Moreover, the classification between E. coli and Pseudomonas aeruginosa achieved an overall accuracy of 96.5% by the principal component analysis with linear discriminant analysis models. The success of this sensing strategy illustrates its potential in detecting and identifying a variety of biomarkers present in respiratory aerosols, marking a significant step forward in the field of pathogen detection.

Material Breakthroughs in Smart Food Monitoring: Intelligent Packaging and On-Site Testing Technologies for Spoilage and Contamination Detection

Despite extensive commercial and regulatory interventions, food spoilage and contamination continue to impose massive ramifications on human health and the global economy. Recognizing that such issues will be significantly eliminated by the accurate and timely monitoring of food quality markers, smart food sensors have garnered significant interest as platforms for both real-time, in-package food monitoring and on-site commercial testing. In both cases, the sensitivity, stability, and efficiency of the developed sensors are largely informed by underlying material design, driving focus toward the creation of advanced materials optimized for such applications. Herein, a comprehensive review of emerging intelligent materials and sensors developed in this space is provided, through the lens of three key food quality markers - biogenic amines, pH, and pathogenic microbes. Each sensing platform is presented with targeted consideration toward the contributions of the underlying metallic or polymeric substrate to the sensing mechanism and detection performance. Further, the real-world applicability of presented works is considered with respect to their capabilities, regulatory adherence, and commercial potential. Finally, a situational assessment of the current state of intelligent food monitoring technologies is provided, discussing material-centric strategies to address their existing limitations, regulatory concerns, and commercial considerations.

A simple, sensitive and colorimetric assay for Pseudomonas aeruginosa infection analysis

Skin and soft tissue infections caused by Pseudomonas aeruginosa are common acquired diseases in postpartum care. Many methods have been developed in recent years for detecting P. aeruginosa, but they are criticized for the drawbacks of labor-intensiveness, complicated operation and high cost. Here, a simple, sensitive and colorimetric assay for P. aeruginosa detection is described. The approach displays a green color for positive samples and colorless for target-free samples. The approach exhibits a wide detection range and a low limit of detection of 45 CFU/ml. Thus, the developed ligation-initiated multiple-signal amplification method may be used for on-site testing of pathogenic bacteria and assist in the early diagnosis of postpartum care skin infections.

Rapid In Vitro Assessment of Antimicrobial Drug Effect Bridging Clinically Relevant Pharmacokinetics: A Comprehensive Methodology

Rapid in vitro assessment of antimicrobial drug efficacy under clinically relevant pharmacokinetic conditions is an essential element of both drug development and clinical use. Here, we present a comprehensive overview of a recently developed novel integrated methodology for rapid assessment of such efficacy, particularly against the emergence of resistant bacterial strains, as jointly researched by the authors in recent years. This methodology enables rapid in vitro assessment of the antimicrobial efficacy of single or multiple drugs in combination, following clinically relevant pharmacokinetics. The proposed methodology entails (a) the automated collection of longitudinal time-kill data in an optical-density instrument; (b) the processing of collected time-kill data with the aid of a mathematical model to determine optimal dosing regimens under clinically relevant pharmacokinetics for single or multiple drugs; and (c) in vitro validation of promising dosing regimens in a hollow fiber system. Proof-of-concept of this methodology through a number of in vitro studies is discussed. Future directions for the refinement of optimal data collection and processing are discussed.

Fast identification and susceptibility determination of E. coli isolated directly from patients' urine using infrared-spectroscopy and machine learning

For effective treatment, it is crucial to identify the infecting bacterium at the species level and to determine its antimicrobial susceptibility. This is especially true now, when numerous bacteria have developed multidrug resistance to most commonly used antibiotics. Currently used methods need ∼ 48 h to identify a bacterium and determine its susceptibility to specific antibiotics. This study reports the potential of using infrared spectroscopy with machine learning algorithms to identify E. coli isolated directly from patients' urine while simultaneously determining its susceptibility to antibiotics within ∼ 40 min after receiving the patient's urine sample. For this goal, 1,765 E. coli isolates purified directly from urine samples were collected from patients with urinary tract infections (UTIs). After collection, the samples were tested by infrared microscopy and analyzed by machine learning. We achieved success rates of ∼ 96% in isolate level identification and ∼ 84% in susceptibility determination.

Rapid detection of bacteria using gold nanoparticles in SERS with three different capping agents: Thioglucose, polyvinylpyrrolidone, and citrate

The increase in outbreaks of emerging and re-emerging bacterial infections over the last few decades calls for their rapid detection and treatment. Surface-enhanced Raman spectroscopy (SERS) is a technique that can be applied to develop fast screening systems for bacterial presence in biological samples. Optimizing the capping agents in nanoparticle synthesis is important because capping agents are responsible for controlling the morphological features and chemical properties of the nanoparticles that are essential for SERS. To the best of our knowledge, this paper is the first to study the application of gold nanoparticles capped with thioglucose and polyvinylpyrrolidone (PVP) in SERS detection of bacteria as an alternative to the citrate-capped gold nanoparticles that are often used in SERS detection of bacteria. Three different species of bacteria were used in this study: Cutibacterium acnes, Escherichia coli and Staphylococcus aureus (methicillin-sensitive and methicillin-resistant). This study demonstrates that the thioglucose, citrate both show good contribution in bacterial species identification and the thioglucose shows the best among the three capping agents in two types of S. aureus identification. Moreover, although PVP showed high Raman peaks in the SERS spectrum for each type of bacteria, it showed least contribution in identifying species and strains due to its low efficacy in producing responses from different nucleic acid components in the bacteria cells.

CRISPR/dCas9-surface-enhanced Raman scattering for the detection of drug resistance gene macB

Antibiotics have brought many benefits to public health systems worldwide since their first use in the last century, yet with their overuse in clinical treatment and livestock farming, new public health issues have arisen. Previously, we found in our experiments that the levels of macB genes in bovine raw milk ranked among the top of many drug resistance genes. In this paper, we present an analysis of regularly interspaced clustered short palindromic repeats (CRISPR) combined with surface-enhanced Raman scattering (SERS) technology for the detection of the drug resistance gene macB. The analysis was accomplished through the collaboration of the CRISPR system's ability to specifically identify genes and the more sensitive performance of the SERS. The analysis detects the drug resistance gene macB and does not yet require complex steps such as nucleic acid amplification. This method may prove to be an effective method for accurate detection of the drug-resistant gene macB, thus enabling more effective prevention of contamination of drug-resistant genes in food hygiene.

A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements

With the acceleration of urbanization and living standards, microorganisms play an increasingly important role in industrial production, bio-technique, and food safety testing. Microorganism biovolume measurements are one of the essential parts of microbial analysis. However, traditional manual measurement methods are time-consuming and challenging to measure the characteristics precisely. With the development of digital image processing techniques, the characteristics of the microbial population can be detected and quantified. The applications of the microorganism biovolume measurement method have developed since the 1980s. More than 62 articles are reviewed in this study, and the articles are grouped by digital image analysis methods with time. This study has high research significance and application value, which can be referred to as microbial researchers to comprehensively understand microorganism biovolume measurements using digital image analysis methods and potential applications.

A Comprehensive Analysis of ATP Tests: Practical Use and Recent Progress in the Total Adenylate Test for the Effective Monitoring of Hygiene

ABSTRACT

Rapid hygiene monitoring tests based on the presence of ATP have been widely used in the food industry to ensure that adequate cleanliness is maintained. In this study, the practical applications and limitations of these tests and recent technological progress for facilitating more accurate control were evaluated. The presence of ATP on a surface indicates improper cleaning and the presence of contaminants, including organic debris and bacteria. Food residues are indicators of insufficient cleaning and are direct hazards because they may provide safe harbors for bacteria, provide sources of nutrients for bacterial growth, interfere with the antimicrobial activity of disinfectants, and support the formation of biofilms. Residues of allergenic foods on a surface may increase the risk of allergen cross-contact. However, ATP tests cannot detect bacteria or allergenic proteins directly. To ensure efficient use of commercially available ATP tests, in-depth knowledge is needed regarding their practical applications, methods for determining pass-fail limits, and differences in performance. Conventional ATP tests have limitations due to possible hydrolysis of ATP to ADP and AMP, which further hinders the identification of food residues. To overcome this problem, a total adenylate test was developed that could detect ATP+ADP+AMP (A3 test). The A3 test is suitable for the detection of adenylates from food residues and useful for verification of hygiene levels. The A3 test in conjunction with other methods, such as microorganism culture and food allergen tests, may be a useful strategy for identifying contamination sources and facilitating effective hygiene management.

HIGHLIGHTS

Present and pioneer methods of early detection of food borne pathogens

Food-borne pathogens are a severe threat to human illness and death world-wide. Researchers have reported more than 250 food-borne diseases. Most of these are infections caused by a wide variety of bacteria, viruses, and parasites. It has a significant economic impact also. Detection of pathogenic microbes is thus essential for food safety. Such identification techniques could meet the following parameters viz., the accuracy of detection techniques that are quick, efficient, economical, highly sensitive, specific, and non-labor intensive. The various available methods for detecting food pathogens are classified into different groups, each having its advantages and disadvantages. The conventional methods are usually the first choice of detection even though they are laborious. Modern techniques such as biosensors, immunological assays, and macromolecule-based (nucleic acid) methods are being developed and refined to overcome traditional methods' limitations. Early detection of pathogens and secure food safety at each stage of food processing to storage, utilizing improved methodologies are mandatory. This review summarizes the deadly food pathogens leading to significant outbreaks and discusses the importance of early detection methods and advanced detection methods in comparison.

Imprinted Polydimethylsiloxane-Graphene Oxide Composite Receptor for the Biomimetic Thermal Sensing of Escherichia coli

This work presents an imprinted polymer-based thermal biomimetic sensor for the detection of Escherichia coli. A novel and facile bacteria imprinting protocol for polydimethylsiloxane (PDMS) films was investigated, and these receptor layers were functionalized with graphene oxide (GO) in order to improve the overall sensitivity of the sensor. Upon the recognition and binding of the target to the densely imprinted polymers, a concentration-dependent measurable change in temperature was observed. The limit of detection attained for the sensor employing PDMS-GO imprints was 80 ± 10 CFU/mL, a full order lower than neat PDMS imprints (670 ± 140 CFU/mL), illustrating the beneficial effect of the dopant on the thermo-dynamical properties of the interfacial layer. A parallel benchmarking of the thermal sensor with a commercial impedance analyzer was performed in order to prove the possibility of using the developed PDMS-GO receptors with multiple readout platforms. Moreover, S. aureus, C. sakazakii and an additional E. coli strain were employed as analogue species for the assessment of the selectivity of the device. Finally, because of the potential that this biomimetic platform possesses as a low-cost, rapid, and on-site tool for monitoring E. coli contamination in food safety applications, spiked fruit juice was analyzed as a real sample. Reproducible and sensitive results fulfill the limit requirements of the applicable European microbiological regulation.

Microfluidic One-Pot Digital Droplet FISH Using LNA/DNA Molecular Beacons for Bacteria Detection and Absolute Quantification

We demonstrate detection and quantification of bacterial load with a novel microfluidic one-pot wash-free fluorescence in situ hybridization (FISH) assay in droplets. The method offers minimal manual workload by only requiring mixing of the sample with reagents and loading it into a microfluidic cartridge. By centrifugal microfluidic step emulsification, our method partitioned the sample into 210 pL (73 µm in diameter) droplets for bacterial encapsulation followed by in situ permeabilization, hybridization, and signal detection. Employing locked nucleic acid (LNA)/DNA molecular beacons (LNA/DNA MBs) and NaCl-urea based hybridization buffer, the assay was characterized with Escherichia coli, Klebsiella pneumonia, and Proteus mirabilis. The assay performed with single-cell sensitivity, a 4-log dynamic range from a lower limit of quantification (LLOQ) at ~3 × 10³ bacteria/mL to an upper limit of quantification (ULOQ) at ~3 × 10⁷ bacteria/mL, anda linearity R² = 0.976. The total time-to-results for detection and quantification was around 1.5 hours.

Recent Advances and Applications of Rapid Microbial Assessment from a Food Safety Perspective

Unsafe food is estimated to cause 600 million cases of foodborne disease, annually. Thus, the development of methods that could assist in the prevention of foodborne diseases is of high interest. This review summarizes the recent progress toward rapid microbial assessment through (i) spectroscopic techniques, (ii) spectral imaging techniques, (iii) biosensors and (iv) sensors designed to mimic human senses. These methods often produce complex and high-dimensional data that cannot be analyzed with conventional statistical methods. Multivariate statistics and machine learning approaches seemed to be valuable for these methods so as to "translate" measurements to microbial estimations. However, a great proportion of the models reported in the literature misuse these approaches, which may lead to models with low predictive power under generic conditions. Overall, all the methods showed great potential for rapid microbial assessment. Biosensors are closer to wide-scale implementation followed by spectroscopic techniques and then by spectral imaging techniques and sensors designed to mimic human senses.

Rapid photothermal detection of foodborne pathogens based on the aggregation of MPBA-AuNPs induced by MPBA using a thermometer as a readout

Rapid and portable detection of foodborne pathogens is of great significance for food safety and public health. The colorimetric methods based on naked-eye have been demonstrated to be a suitable qualitative method for point-of-care testing (POCT). However, analytical instruments like a microplate reader must be needed for the quantitative assay. To overcome its limitation, we herein report a novel photothermal method for foodborne pathogens based on the photothermal effect of aggregated mercaptophenylboronic acid-functionalized AuNPs (MPBA-AuNPs) induced by MPBA to translate the colorimetric detection into a simple temperature measurement using thermometers as the readout. The aggregated AuNPs show higher photothermal conversion efficiency than well-separated AuNPs under 660 nm laser irradiation. In the presence of bacteria, MPBA-AuNPs will attach to the surface of bacteria and keep separated from aggregation induced by excess MPBA, resulting in a lower temperature increase under 660 nm laser irradiation. Using E. coli O157:H7 as a model target, a good linear relationship is observed between temperature increase and bacteria concentration from 1.00 × 10⁵-1.00 × 10⁹ cfu mL^-1 (R² = 0.9877) with a detection limit of 1.97 × 10⁴ cfu mL^-1, which is three orders of magnitude lower than of the MPBA-AuNPs-based colorimetric assays. The proposed photothermal method provided a universal platform for rapid and portable detection of broad-spectrum bacteria strains in real samples.

Quantitative Imaging of Bacteriophage Amplification for Rapid Detection of Bacteria in Model Foods

Rapid detection of bacteria in water and food samples is a critical need. The current molecular methods like real-time PCR can provide rapid detection after initial enrichment. However, these methods require significant preparation steps, specialized facilities to reduce contamination, and relatively expensive reagents. This study evaluates a novel approach for detecting bacteria based on imaging of bacteriophage amplification upon infection of the target host bacteria to mitigate some of these constraints and improve the specificity of discriminating live vs. dead bacteria. Thus, this research leverages the natural ability of lytic bacteriophages to rapidly amplify their genetic material and generate progeny phages upon infecting the host bacterium. This study uses a nucleic acid staining dye, a conventional fluorescence microscope, and quantitative image analysis for imaging the amplification of bacteriophages. The sensitivity and assay time for imaging-based quantification of phage amplification for detecting Escherichia coli were compared with RT-PCR and the standard plaque-forming assay for detection phage amplification in model systems, including coconut water and spinach wash water. The results demonstrate that the imaging approach matches both the sensitivity and speed for detecting E. coli using the RT-PCR method without requiring isolation of nucleic acids, expensive reagents, and specialized facilities. The quantitative imaging results demonstrate the detection of 10 CFU/ml of E. coli in coconut water and simulated spinach wash water with a chemical oxygen demand (COD) of 3,000 ppm within 8 h, including initial enrichment of the bacteria. In summary, the results of this study illustrate a novel phage amplification-based approach for detecting target bacteria in complex food and water samples using simple sample preparation methods and low-cost reagents.

Biosensors and Point-of-Care Devices for Bacterial Detection: Rapid Diagnostics Informing Antibiotic Therapy

With an exponential rise in antimicrobial resistance and stagnant antibiotic development pipeline, there is, more than ever, a crucial need to optimize current infection therapy approaches. One of the most important stages in this process requires rapid and effective identification of pathogenic bacteria responsible for diseases. Current gold standard techniques of bacterial detection include culture methods, polymerase chain reactions, and immunoassays. However, their use is fraught with downsides with high turnaround time and low accuracy being the most prominent. This imposes great limitations on their eventual application as point-of-care devices. Over time, innovative detection techniques have been proposed and developed to curb these drawbacks. In this review, a systematic summary of a range of biosensing platforms is provided with a strong focus on technologies conferring high detection sensitivity and specificity. A thorough analysis is performed and the benefits and drawbacks of each type of biosensor are highlighted, the factors influencing their potential as point-of-care devices are discussed, and the authors' insights for their translation from proof-of-concept systems into commercial medical devices are provided.

Discerning in vitro pharmacodynamics from OD measurements: A model-based approach

Time-kill experiments can discern the pharmacodynamics of infectious bacteria exposed to antibiotics in vitro, and thus help guide the design of effective therapies for challenging clinical infections. This task is resource-limited, therefore typically bypassed in favor of empirical shortcuts. The resource limitation could be addressed by continuously assessing the size of a bacterial population under antibiotic exposure using optical density measurements. However, such measurements count both live and dead cells and are therefore unsuitable for declining populations of live cells. To fill this void, we develop here a model-based method that infers the count of live cells in a bacterial population exposed to antibiotics from continuous optical-density measurements of both live and dead cells combined. The method makes no assumptions about the underlying mechanisms that confer resistance and is widely applicable. Use of the method is demonstrated by an experimental study on Acinetobacter baumannii exposed to levofloxacin.

N, O-codoped hierarchical porous graphitic carbon for electrochemical immunosensing of Lactobacillus rhamnosus GG

An ultrasensitive label-free electrochemical immunosensor was fabricated for quantitative detection of Lactobacillus rhamnosus GG (LGG). The N/O co-doped three-dimensional hierarchical porous graphitic (THPG) carbon was synthesized by a one-step synthesis of polyaniline hydrogel, and followed by simple carbonization and chemical activation procedures. Because of the unique structure design, the obtained THPG carbon networks possess an ultra-large specific surface area of 4859 m² g^-1 along with a class of highly graphitic carbons. The results offer an enormous surface area and excellent electrical conductivity for label-free electrochemical immunosensing of probiotic L. rhamnosus strain. Under optimal conditions, the immunosensor showed a good linear relationship between peak current and concentration of LGG (R² = 0.9976), with a detection limit of 2 CFU mL^-1. Furthermore, this label-free immunosensor also shows good specificity, long-term stability, and reliability, and could be applied to detect probiotic LGG in dairy products and drinks with satisfactory results. The present protocol was shown to be quite promising for practical screening and functional evaluation of probiotic products containing LGG. A ultrasensitive label-free electrochemical immunosensor based on THPG carbon was fabricated for detection of Lactobacillus rhamnosus GG.

Deep Learning Assisted Microfluidic Impedance Flow Cytometry for Label-free Foodborne Bacteria Analysis and Classification. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021;2021:7087-7090. [PMID: 34892734 DOI: 10.1109/embc46164.2021.9630684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

According to the urgent need for rapid detection and identification of foodborne bacteria to prevent public health event, a microfluidic electrical impedance flow cytometry assisted with convolutional neural network (ConvNet) based deep learning algorithm was proposed in this study to analyze the impedance signals of bacteria. With the assistance of the deep learning algorithm, Escherichia coli (EPEC), Salmonella enteritidis (SE) and Vibrio parahaemolyticus (VP) were identified with an accuracy of 100%. The proposed impedance based analysis system can be potentially applied for pre-classification of different subtypes of bacteria in a label-free manner.Clinical Relevance-The whole platform can be miniaturized and applied for point-of-care testing (POCT) of pathogenic bacteria detection.

Surface enhanced Raman scattering for the multiplexed detection of pathogenic microorganisms: towards point-of-use applications

Surface enhanced Raman scattering (SERS) is a technique that demonstrates a number of advantages for the rapid, specific and sensitive detection of pathogenic microorganisms. In this review, an overview of label-free and label-based SERS approaches, including microfluidics, nucleic acid detection and immunoassays, for the multiplexed detection of pathogenic bacteria and viruses from the last decade will be discussed, as well as their transition into promising point-of-use detection technologies in industrial and medical settings.

A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches

Microorganisms such as bacteria and fungi play essential roles in many application fields, like biotechnique, medical technique and industrial domain. Microorganism counting techniques are crucial in microorganism analysis, helping biologists and related researchers quantitatively analyze the microorganisms and calculate their characteristics, such as biomass concentration and biological activity. However, traditional microorganism manual counting methods, such as plate counting method, hemocytometry and turbidimetry, are time-consuming, subjective and need complex operations, which are difficult to be applied in large-scale applications. In order to improve this situation, image analysis is applied for microorganism counting since the 1980s, which consists of digital image processing, image segmentation, image classification and suchlike. Image analysis-based microorganism counting methods are efficient comparing with traditional plate counting methods. In this article, we have studied the development of microorganism counting methods using digital image analysis. Firstly, the microorganisms are grouped as bacteria and other microorganisms. Then, the related articles are summarized based on image segmentation methods. Each part of the article is reviewed by methodologies. Moreover, commonly used image processing methods for microorganism counting are summarized and analyzed to find common technological points. More than 144 papers are outlined in this article. In conclusion, this paper provides new ideas for the future development trend of microorganism counting, and provides systematic suggestions for implementing integrated microorganism counting systems in the future. Researchers in other fields can refer to the techniques analyzed in this paper.

High resolution and rapid separation of bacteria from blood using elasto-inertial microfluidics

Improved sample preparation has the potential to address unmet needs for fast turnaround sepsis tests. In this work, we report elasto-inertial based rapid bacteria separation from diluted blood at high separation efficiency. In viscoelastic flows, we demonstrate novel findings where blood cells prepositioned at the outer wall entering a spiral device remain fully focused throughout the channel length while smaller bacteria migrate to the opposite wall. Initially, using microparticles, we show that particles above a certain size cut-off remain fully focused at the outer wall while smaller particles differentially migrate toward the inner wall. We demonstrate particle separation at 1 μm resolution at a total throughput of 1 mL/min. For blood-based experiments, a minimum of 1:2 dilution was necessary to fully focus blood cells at the outer wall. Finally, Escherichia coli spiked in diluted blood were continuously separated at a total flow rate of 1 mL/min, with efficiencies between 82 and 90% depending on the blood dilution. Using a single spiral, it takes 40 min to process 1 mL of blood at a separation efficiency of 82%. The label-free, passive, and rapid bacteria isolation method has a great potential for speeding up downstream phenotypic and genotypic analysis.

Occurrence and distribution of fecal indicators and pathogenic bacteria in seawater and Perna perna mussel in the Gulf of Annaba (Southern Mediterranean)

The identification of fecal contamination in coastal marine ecosystems is one of the main requirements for evaluation of potential risks to human health. The objective of this study was to investigate the occurrence and distribution of fecal indicators and pathogenic bacteria in seawaters and mussels collected monthly during a period of 1 year from four different sites in Northeastern Algeria (sites S1 to S4), through biochemical and molecular analyses. Our research is the first to use molecular analysis to unambiguously identify the potentially pathogenic bacteria present in Algerian Perna perna mussels. The obtained results revealed that the levels of fecal indicator bacteria (FIB) from both P. perna and seawater samples largely exceeded the permissible limits at S2 and S3. This is mainly related to their location close to industrial and coastal activity zones, which contain a mixture of urban, agricultural, and industrial pollutants. Besides, P. perna collected from all sites were severalfold more contaminated by FIB than seawater samples, primarily during the warm season of the study period. Biochemical and molecular analyses showed that isolated bacteria from both seawater and mussels were mainly potentially pathogenic species such as E. coli, Salmonella spp., Staphylococcus spp., Klebsiella spp., Pseudomonas spp., and Proteus spp.

Culture-free biphasic approach for sensitive detection of Escherichia coli O157:H7 from beef samples

Foodborne illnesses are a major threat to public health also leading to significant mortality and financial and reputational damage to industry. It is very important to detect pathogen presence in food products early, rapidly, and accurately to avoid potential outbreaks and economic loss. However, "gold standard" culture methods, including enrichment of pathogens, can take up to several days. Moreover, the food matrix often interferes with nucleic acid amplification methods of detection, requiring DNA extraction from the sample for successful molecular detection of pathogens. Here, we introduce a "biphasic" amplification method that can achieve high sensitivity detection with background noise from ground beef food samples without culture or other extraction methods in 2.5 h. Homogenized ground beef is dried resulting in an increase in porosity of the dried food matrix to allowing amplification enzymes and primers to access the target DNA and initiate the reaction within the dried food matrix. Using Loop Mediated Isothermal Amplification, we demonstrate the detection of 1-3 cfu of Escherichia coli bacteria in 30 mg of dried food matrix. Our approach significantly lowers the time to result to less than a few hours and have a pronounced impact on reduction of instrumentation complexity and costs.

Rapid bacteria-detection platform based on magnetophoretic concentration, dielectrophoretic separation, and impedimetric detection

Most biosensors employ small sample quantities (less than 100 μL) for bacteria detection, thereby resulting in inaccurate low-concentration measurements. Detection performed using small sample volumes with low bacteria concentration may produce false-negative results. Therefore, sample pretreatment plays a critical role in accurate bacteria detection. This paper presents an impedimetric bacteria-detection sensor integrated with bacteria concentration and separation devices for rapid bacteria detection. Post conjugation using magnetic particles (MPs), the MP-conjugated bacteria (MP/Bac) are concentrated via magnetophoresis by a factor exceeding 100. In addition, MP/Bac are separated from MPs via dielectrophoresis to prevent occurrence of signal errors caused by MPs not conjugated with bacteria. Subsequently, concentrated MP/Bac are captured on a sensor electrode, and bacteria concentration is detected by measuring signal changes caused by the impedance difference between bacteria and the medium. The performance of the proposed bacteria-detection device was evaluated using a 5-mL homogenized cabbage sample injected with Staphylococcus aureus at 30 mL/h flow rate. The observed signal change was measured for 10 min using a sample with a concentration of 5-5 × 10³ CFU/mL and was found to be approximately 0.34 mV at 50 CFU/mL; the limit of detection was 36 CFU/mL. These results confirm that the proposed device can detect low bacteria concentrations in food samples.

Development of pattern recognition based on nanosheet-DNA probes and an extendable DNA library

Pattern recognition, also called "array sensing," is a recognition strategy with a wide and expandable analysis range, based on high-throughput analysis data. In this work, we constructed a sensor array for the identification of targets including bacterial pathogens and proteins by using FAM-labeled DNA probes and 2D nanosheet materials. We designed an ordered and extendible DNA library for the collection of recognition probes. Unlike traditional DNA probes with random and massive sequences, our DNA library was constructed following a 5-digit binary number (00000-11111, 0 = CCC, and 1 = TTT), and especially, 8 special symmetry sequences were chosen from the library. Two different nanosheet materials were used as the quencher. When targets were added, the interaction between DNA and the nanosheets was competitively affected, and as a result, the fluorescence signal changed accordingly. Finally, by using our fluorescent sensor array, 17 bacteria and 8 proteins were precisely recognized. We believe that our work has provided a simple and valuable strategy for the improvement of the recognition range and discrimination precision for the development of pattern recognition.

Rapid detection and enumeration of aerobic mesophiles in raw foods using dielectrophoresis

The concept of dielectrophoresis (DEP), which involves the movement of neutral particles by induced polarization in nonuniform electric fields, has been exploited in various biological applications. However, only a few studies have investigated the use of DEP for detecting and enumerating microorganisms in foodstuffs. Therefore, we aimed to evaluate the accuracy and efficiency of a DEP-based method for enumerating viable bacteria in three raw foods: freshly cut lettuce, chicken breast, and minced pork. The DEP separation of bacterial cells was conducted at 20 V of output voltage and 6000 to 9000 kHZ of frequency with sample conductivity of 30-70 μS/cm. The accuracy and validity of the DEP method for enumerating viable bacteria were compared with those of the conventional culture method; no significant variation was observed. We found a high correlation between the data obtained using DEP and the conventional aerobic plate count culture method, with a high coefficient of determination (R2 > 0.90) regardless of the food product; the difference in cell count data between both methods was within 1.0 log CFU/mL. Moreover, we evaluated the efficiency of the DEP method for enumerating bacterial cells in chicken breasts subjected to either freezing or heat treatment. After thermal treatment at 55 °C and 60 °C, the viable cell counts determined via the DEP method were found to be lower than those obtained using the conventional culture method, which implies that the DEP method may not be suitable for the direct detection of injured cells. In addition to its high accuracy and efficiency, the DEP method enables the determination of viable cell counts within 30 min, compared to 48 h required for the conventional culture method. In conclusion, the DEP method may be a potential alternative tool for rapid determination of viable bacteria in a variety of foodstuffs.

A Potentiometric Electronic Tongue as a Discrimination Tool of Water-Food Indicator/Contamination Bacteria

Microorganism assessment plays a key role in food quality and safety control but conventional techniques are costly and/or time consuming. Alternatively, electronic tongues (E-tongues) can fulfill this critical task. Thus, a potentiometric lab-made E-tongue (40 lipid sensor membranes) was used to differentiate four common food contamination bacteria, including two Gram positive (Enterococcus faecalis, Staphylococcus aureus) and two Gram negative (Escherichia coli, Pseudomonas aeruginosa). Principal component analysis and a linear discriminant analysis-simulated annealing algorithm (LDA-SA) showed that the potentiometric signal profiles acquired during the analysis of aqueous solutions containing known amounts of each studied bacteria allowed a satisfactory differentiation of the four bacterial strains. An E-tongue-LDA-SA model (12 non-redundant sensors) correctly classified 98 ± 5% of the samples (repeated K-fold-CV), the satisfactory performance of which can be attributed to the capability of the lipid membranes to establish electrostatic interactions/hydrogen bonds with hydroxyl, amine and/or carbonyl groups, which are comprised in the bacteria outer membranes. Furthermore, multiple linear regression models, based on selected subsets of E-tongue sensors (12–15 sensors), also allowed quantifying the bacteria contents in aqueous solutions (0.993 ± 0.011 ≤ R2 ≤ 0.998 ± 0.005, for repeated K-fold-CV). In conclusion, the E-tongue could be of great value as a preliminary food quality and safety diagnosis tool.

Real-Time In Vivo Detection and Monitoring of Bacterial Infection Based on NIR-II Imaging

Treatment according to the dynamic changes of bacterial load in vivo is critical for preventing progression of bacterial infections. Here, we present a lead sulfide quantum dots (PbS QDs) based second near-infrared (NIR-II) fluorescence imaging strategy for bacteria detection and real-time in vivo monitoring. Four strains of bacteria were labeled with synthesized PbS QDs which showed high bacteria labeling efficiency in vitro. Then bacteria at different concentrations were injected subcutaneously on the back of male nude mice for in vivo imaging. A series of NIR-II images taken at a predetermined time manner demonstrated changing patterns of photoluminescence (PL) intensity of infected sites, dynamically imaging a changing bacterial load in real-time. A detection limit around 10²–10⁴ CFU/ml was also achieved in vivo. Furthermore, analysis of pathology of infected sites were performed, which showed high biocompatibility of PbS QDs. Therefore, under the guidance of our developed NIR-II imaging system, real-time detection and spatiotemporal monitoring of bacterial infection in vivo can be achieved, thus facilitating anti-infection treatment under the guidance of the dynamic imaging of bacterial load in future.

A Bioinspired Peptide in TIR Protein as Recognition Molecule on Electrochemical Biosensors for the Detection of E. coli O157:H7 in an Aqueous Matrix

Currently, the detection of pathogens such as Escherichia coli through instrumental alternatives with fast response and excellent sensitivity and selectivity are being studied. Biosensors are systems consisting of nanomaterials and biomolecules that exhibit remarkable properties such as simplicity, portable, affordable, user‑friendly, and deliverable to end‑users. For this, in this work we report for the first time, to our knowledge, the bioinformatic design of a new peptide based on TIR protein, a receptor of Intimin membrane protein which is characteristic of E. coli. This peptide (named PEPTIR‑1.0) was used as recognition element in a biosensor based on AuNPs‑modified screen‑printed electrodes for the detection of E. coli. The morphological and electrochemical characteristics of the biosensor obtained were studied. Results show that the biosensor can detect the bacteria with limits of detection and quantification of 2 and 6 CFU/mL, respectively. Moreover, the selectivity of the system is statistically significant towards the detection of the pathogen in the presence of other microorganisms such as P. aeruginosa and S. aureus. This makes this new PEPTIR‑1.0 based biosensor can be used in the rapid, sensitive, and selective detection of E. coli in aqueous matrices.

Detection of Bacterial Metabolic Volatile Indole Using a Graphene-Based Field-Effect Transistor Biosensor

The existence of bacteria is a great threat to food safety. Volatile compounds secreted by bacteria during their metabolic process can be dissected to evaluate bacterial contamination. Indole, as a major volatile molecule released by Escherichia coli (E. coli), was chosen to examine the presence of E. coli in this research. In this work, a graphene field-effect transistor (G-FET) was employed to detect the volatile molecule-indole based on a π-π stacking interaction between the indole and the graphene. The exposure of G-FET devices to the indole provokes a change in electrical signal, which is ascribed to the adsorption of the indole molecule onto the graphene surface via π-π stacking. The adsorption of the indole causes a charge rearrangement of the graphene-indole complex, which leads to changes in the electrical signal of G-FET biosensors with a different indole concentration. Currently, the indole biosensor can detect indole from 10 ppb to 250 ppb and reach a limit of detection of 10 ppb for indole solution detection. We believe that our detection strategy for detecting bacterial metabolic gas molecules will pave a way to developing an effective platform for bacteria detection in food safety monitoring.

Modernization of Control of Pathogenic Micro-Organisms in the Food-Chain Requires a Durable Role for Immunoaffinity-Based Detection Methodology-A Review

Food microbiology is deluged by a vastly growing plethora of analytical methods. This review endeavors to color the context into which methodology has to fit and underlines the importance of sampling and sample treatment. The context is that the highest risk of food contamination is through the animal and human fecal route with a majority of foodborne infections originating from sources in mass and domestic kitchens at the end of the food-chain. Containment requires easy-to-use, failsafe, single-use tests giving an overall risk score in situ. Conversely, progressive food-safety systems are relying increasingly on early assessment of batches and groups involving risk-based sampling, monitoring environment and herd/flock health status, and (historic) food-chain information. Accordingly, responsible field laboratories prefer specificity, multi-analyte, and high-throughput procedures. Under certain etiological and epidemiological circumstances, indirect antigen immunoaffinity assays outperform the diagnostic sensitivity and diagnostic specificity of e.g., nucleic acid sequence-based assays. The current bulk of testing involves therefore ante- and post-mortem probing of humoral response to several pathogens. In this review, the inclusion of immunoglobulins against additional invasive micro-organisms indicating the level of hygiene and ergo public health risks in tests is advocated. Immunomagnetic separation, immunochromatography, immunosensor, microsphere array, lab-on-a-chip/disc platforms increasingly in combination with nanotechnologies, are discussed. The heuristic development of portable and ambulant microfluidic devices is intriguing and promising. Tant pis, many new platforms seem unattainable as the industry standard. Comparability of results with those of reference methods hinders the implementation of new technologies. Whatever the scientific and technological excellence and incentives, the decision-maker determines this implementation after weighing mainly costs and business risks.

A simple paper-based colorimetric analytical device for rapid detection of Enterococcus faecalis under the stress of chlorophenols

Bacteria detection and toxicity measurement are essential in many aspects. Becoming increasingly popular in recent years, paper-based analytical devices (PADs) have proven to be cost-effective, portable and eco-friendly with quantitative diagnostic results. In this work, by a straightforward soaking-drying method, a resazurin-deposited PAD has been developed for rapid bacteria detection and biotoxicity measurement. The colorimetric response on the PAD was generated from metabolic reduction of resazurin by Enterococcus faecalis, a facultative anaerobic bacterial strain. After recording and quantifying the colorimetric response with Hue value by a smartphone, the bioassay on PAD enables the detection of resazurin reduction kinetics difference among bacteria at various densities in 10 min. Thereby, the bioassay on PAD was applied to study the toxicity of two chlorophenols, i.e. pentachlorophenol (PCP) and 4-chlorophenol (4-CP), to E. faecalis. Compared to growth-based inhibition test, which takes 5 h, this assay shows higher efficiency, i.e. in 30 min, the biotoxicity difference between PCP and 4-CP can be identified.

Enzyme embedded microfluidic paper-based analytic device (μPAD): a comprehensive review

Low-cost paper-based analytical devices are the latest generation of portable lab-on-chip designs that offers an innovative platform for the on/off-site analysis (biosensing) of target analytes, especially in rural and remote areas. Recently, microfluidic paper-based analytical devices (μPADs) have attained significant recognition owing to their exciting fundamental features such as: ease of fabrication, rapid operation, and precise interpretations. The incorporation of enzymes with paper-based analytical devices significantly improves analytical performance while exhibiting excellent chemical and storage stability. In addition to that, these devices are highly compact, portable, easy-to-use, and do not require any additional sophisticated equipment for the detection and quantification of target analytes. This review provides a holistic insight into design, fabrication, and enzyme immobilization strategies for the development of enzyme-μPADs, which enables them to be widely implemented for in-field analysis. It also highlights the recent application of enzyme-μPADs in the area of: biomedical, food safety, and environmental monitoring while exploring the mechanisms of detection involved. Further, in order to improve the accuracy of analysis, researchers have designed a smartphone-based scanning tool for multi-variant point-of-care devices, which is summarized in the latter part of the review. Finally, the future perspectives and outlook of major challenges associated with enzyme-μPADs are discussed with their possible solutions. The development of enzyme integrated μPADs will open a new avenue as an exceptional analytical tool to explore various applications.HIGHLIGHTSEnzyme embedded paper-based analytical devices are a revolution in the field of biosensing.The design, fabrication, and enzyme immobilization on μPADs have been comprehensively discussed.The application of enzyme-μPADs food safety, environmental monitoring, and clinical diagnostic have been reviewed.Smartphones can be used as an on-site, user-friendly, and compact next-gen scanning tool for biosensing.

Imprinted Polymers as Synthetic Receptors in Sensors for Food Safety

Foodborne illnesses represent high costs worldwide in terms of medical care and productivity. To ensure safety along the food chain, technologies that help to monitor and improve food preservation have emerged in a multidisciplinary context. These technologies focus on the detection and/or removal of either biological (e.g., bacteria, virus, etc.) or chemical (e.g., drugs and pesticides) safety hazards. Imprinted polymers are synthetic receptors able of recognizing both chemical and biological contaminants. While numerous reviews have focused on the use of these robust materials in extraction and separation applications, little bibliography summarizes the research that has been performed on their coupling to sensing platforms for food safety. The aim of this work is therefore to fill this gap and highlight the multidisciplinary aspects involved in the application of imprinting technology in the whole value chain ranging from IP preparation to integrated sensor systems for the specific recognition and quantification of chemical and microbiological contaminants in food samples.

Clustered Regularly Interspaced Short Palindromic Repeats-Mediated Surface-Enhanced Raman Scattering Assay for Multidrug-Resistant Bacteria

Antimicrobial resistance and multidrug resistance are slower-moving pandemics than the fast-spreading coronavirus disease 2019; however, they have potential to cause a much greater threat to global health. Here, we report a clustered regularly interspaced short palindromic repeats (CRISPR)-mediated surface-enhanced Raman scattering (SERS) assay for multidrug-resistant (MDR) bacteria. This assay was developed via a synergistic combination of the specific gene-recognition ability of the CRISPR system, superb sensitivity of SERS, and simple separation property of magnetic nanoparticles. This assay detects three multidrug-resistant (MDR) bacteria, species Staphylococcus aureus, Acinetobacter baumannii, and Klebsiella pneumoniae, without purification or gene amplification steps. Furthermore, MDR A. baumannii-infected mice were successfully diagnosed using the assay. Finally, we demonstrate the on-site capture and detection of MDR bacteria through a combination of the three-dimensional nanopillar array swab and CRISPR-mediated SERS assay. This method may prove effective for the accurate diagnosis of MDR bacterial pathogens, thus preventing severe infection by ensuring appropriate antibiotic treatment.

Investigating the Use of Impedance Flow Cytometry for Classifying the Viability State of E. coli

Bacteria detection, counting and analysis is of great importance in several fields. When viability plays a major role in decision making, the counting of colony-forming units grown on agar plates remains the gold standard. However, because plate counts depend on the growth of the bacteria, it is a slow procedure and only works with culturable species. Impedance flow cytometry (IFC) is a promising technology for particle detection, counting and characterization. It relies on the perturbation of an electric field by particles flowing through a microfluidic channel. The perturbation is directly related to the electrical properties of the particles, and therefore provides information about their composition and structure. In this work we investigate whether IFC can be used to differentiate viable cells from inactivated cells. Our findings demonstrate that the specific viability state of the bacteria has to be considered, but that with proper characterization thresholds, IFC can be used to classify bacterial viability states. By using three different inactivation methods-ethanol, heat and autoclavation-we have been able to show that the impedance response of Escherichia coli depends on its viability state, but that the specific response depends on the inactivation method. With these findings we expect to be able to optimize IFC for more reliable bacteria detection and counting in the future.