Current and near-future technologies for antibiotic susceptibility testing and resistant bacteria detection

β-Galactosidase-triggered in situ synthesis of yellow emitting silicon nanoparticle and its application in visual detection of E. coli O157:H7 and drug susceptibility test

The sensitive detection of foodborne pathogenic and rapid antibiotic susceptibility testing (AST) is of great significance. This paper reports the enzyme-triggered in situ synthesis of yellow emitting silicon nanoparticles (SiNPs) and the detection of Escherichia coli (E. coli) O157:H7 in food samples and the rapid AST. The rapid counting of E. coli O157:H7 has been achieved through direct visual observation, equipment detection, and smartphone digitalization. A simple detection platform based on smartphone senses and cotton swabs has been established. Meanwhile, rapid AST based on enzyme-catalyzed SiNPs can intuitively obtain colorimetric samples. This paper established a system for bacterial enzyme-triggered in situ synthesis of SiNPs, with high responsiveness, luminescence ratio, and specificity. The detection limit for E. coli O157:H7 can reach 100 CFU/mL during 5 h, and the recovery efficiency ranges from 90.14% to 110.16%, which makes it a promising strategy for the rapid detection of E. coli O157:H7 and AST.

Rapid detection of bactericidal efficacy of nanoparticles coated polyurethane foam by synchronous fluorescence spectroscopy

The ability of right-angled synchronous fluorescence spectroscopy (SFS) was explored to analyse the bacterial load in water treated with green synthesized silver nanoparticles (AgNPs) coated polyurethane foam (PUF). Gram negative (Escherichia coli, Pseudomonas aeruginosa) and Gram positive (Staphylococcus aureus) bacteria cultured in nutrient broth were diluted in autoclaved water containing NPs-coated PUF. The survival rate of S. aureus and E. coli lowered after ten minutes as compared to P. aeruginosa; however, after thirty minutes, the percentage viability dropped and recorded as 3.4%, 0.9%, and 0.1% for E. coli, P. aeruginosa and S. aureus respectively in the treated suspensions. No spectral change was observed in the fluorescence emission from the positive control and treated bacterial suspension owing to the masking effect of the emission from nutrient broth. In parallel, SF spectra recorded for directly picked bacterial colony dissolved in water showed remarkable drop in tryptophan emission after treatment with NPs-coated PUF. The SF data changes were assisted by hierarchical cluster analysis, which also made it possible to distinguish between positive control and treated bacterial suspensions. SFS has shown to be a reliable substitute for the culture plate approach for the quick identification of bacterial contamination in water.

Food-borne bacteria analysis using a diatomite bioinspired SERS platform

Rapid and sensitive detection of food-borne bacteria has remained challenging over the past few decades. We propose a surface-enhanced Raman scattering sensing strategy based on a novel bioinspired surface-enhanced Raman scattering substrate, which can directly detect dye molecular residues and food-borne pathogen microorganisms in the environment. The surface-enhanced Raman scattering platform consists of a natural diatomite microporous array decorated with a metal-phenolic network that enables the in situ reduction of gold nanoparticles. The as-prepared nanocomposites display excellent surface-enhanced Raman scattering activity with the lowest limit of detection and the maximum Raman enhancement factor of dye molecules up to 10-11 M and 1.18 × 107, respectively. For food-borne bacterial detection, a diatomite microporous array decorated with a metal polyphenol network and gold nanoparticle-based surface-enhanced Raman scattering analysis is capable of distinguishing the biochemical fingerprint information of Staphylococcus aureus and Escherichia coli, indicating the great potential for strain identification.

Lipid-based nanoparticles as drug delivery carriers for cancer therapy

Cancer is a severe disease that results in death in all countries of the world. A nano-based drug delivery approach is the best alternative, directly targeting cancer tumor cells with improved drug cellular uptake. Different types of nanoparticle-based drug carriers are advanced for the treatment of cancer, and to increase the therapeutic effectiveness and safety of cancer therapy, many substances have been looked into as drug carriers. Lipid-based nanoparticles (LBNPs) have significantly attracted interest recently. These natural biomolecules that alternate to other polymers are frequently recycled in medicine due to their amphipathic properties. Lipid nanoparticles typically provide a variety of benefits, including biocompatibility and biodegradability. This review covers different classes of LBNPs, including their characterization and different synthesis technologies. This review discusses the most significant advancements in lipid nanoparticle technology and their use in medicine administration. Moreover, the review also emphasized the applications of lipid nanoparticles that are used in different cancer treatment types.

Python-assisted detection and photothermal inactivation of Salmonella typhimurium and Staphylococcus aureus on a background-free SERS chip

In this study, a background-free surface-enhanced Raman scattering (SERS) chip with a sandwich configuration was fabricated to enable reliable detection and photothermal inactivation of multiple bacteria. The SERS chip consists of a graphene-coated, phenylboronic-modified plasmonic gold substrate (pAu/G/PBA), and two aptamer-functionalized core (gold)-shell (Prussian blue/Poly-L-lysine and 4-mercaptobenzonitrile/polydopamine) SERS tags (Au@PB@PLL@Apt and Au@MB@PDA@Apt). The detection signals rely on the characteristic and nonoverlapping Raman bands of the SERS tags within the Raman-silent region (1800-2800 cm-1), where no background signals from the sample matrix are observed, leading to improved detection sensitivity and accuracy. Considering the relatively large size of bacteria (e.g., micron level), a rapid Raman mapping technique was chosen over conventional point-scan methods to achieve more reliable quantitative analysis of bacteria. This technique involves collecting and analyzing intensity signals of SERS tags from all the scattering points with an average ensemble effect, which is facilitated by the use of Python. As a proof-of-concept, model bacterium of Salmonella typhimurium and Staphylococcus aureus were successfully detected using the SERS chip with a dynamic range of 10-107 CFU/mL. Additionally, the SERS chip demonstrated successful detection of these bacteria in whole blood samples. Moreover, the photothermal effect of pAu/G led to efficient bacteria elimination, achieving approximately 100% eradication. This study integrated a background-free SERS chip with a Python-assisted rapid Raman mapping technique, resulting in a reliable, rapid and accurate method for detecting and eliminating multiple bacteria, which may provide a promising alternative for multiple screening of bacteria in real samples.

Electrochemical techniques for label-free and early detection of growing microbial cells and biofilms

Over the past decades, the misuse or abuse of antimicrobial agents to prevent and/or control infections has led to increased resistance of microbes to treatments, and antimicrobial resistance is now a subject of major global concern. In some cases, microbes possess the capacity to attach to biotic or abiotic surfaces, and to produce a protective polymeric matrix, forming biofilms of higher resistance and virulence compared to planktonic forms. To avoid further excessive and inappropriate use of antimicrobials, and to propose new effective treatments, it is very important to detect planktonic microbes and microbial biofilms in their early growth stage and at the point of need. In this review, we provide an overview of currently available electrochemical techniques, in particular impedimetric and voltamperometric methods, highlighting recent advances in the field and illustrating with examples in antibiotic susceptibility testing and microbial biofilm monitoring.

Metabolism-Triggered Plasmonic Nanosensor for Bacterial Detection and Antimicrobial Susceptibility Testing of Clinical Isolates

Antimicrobial resistance (AMR) is predicted to become the leading cause of death worldwide in the coming decades. Rapid and on-site antibiotic susceptibility testing (AST) is crucial for guiding appropriate antibiotic choices to combat AMR. With this in mind, we have designed a simple and efficient plasmonic nanosensor consisting of Cu2+ and cysteine-modified AuNP (Au/Cys) that utilizes the metabolic activity of bacteria toward Cu2+ for bacterial detection and AST. When Cu2+ is present, it induces the aggregation of Au/Cys. However, in the presence of bacteria, Cu2+ is metabolized to varying extents, resulting in distinct levels of aggregation. Moreover, the metabolic activity of bacteria can be influenced by their antibiotic susceptibility, allowing us to differentiate between susceptible and resistant strains through direct color changes from the Cu2+-Au/Cys platform over approximately 3 h. These color changes can be easily detected using naked-eye observation, smartphone analysis, or absorption readout. We have validated the platform using four clinical isolates and six types of antibiotics, demonstrating a clinical sensitivity and specificity of 95.8%. Given its simplicity, low cost, high speed, and high accuracy, the plasmonic nanosensor holds great potential for point-of-care detection of antibiotic susceptibility across various settings.

Recent advances in surface enhanced Raman spectroscopy for bacterial pathogen identifications

BACKGROUND

The rapid and reliable detection of pathogenic bacteria at an early stage is a highly significant research field for public health. However, most traditional approaches for pathogen identification are time-consuming and labour-intensive, which may cause physicians making inappropriate treatment decisions based on an incomplete diagnosis of patients with unknown infections, leading to increased morbidity and mortality. Therefore, novel methods are constantly required to face the emerging challenges of bacterial detection and identification. In particular, Raman spectroscopy (RS) is becoming an attractive method for rapid and accurate detection of bacterial pathogens in recent years, among which the newly developed surface-enhanced Raman spectroscopy (SERS) shows the most promising potential.

AIM OF REVIEW

Recent advances in pathogen detection and diagnosis of bacterial infections were discussed with focuses on the development of the SERS approaches and its applications in complex clinical settings.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The current review describes bacterial classification using surface enhanced Raman spectroscopy (SERS) for developing a rapid and more accurate method for the identification of bacterial pathogens in clinical diagnosis. The initial part of this review gives a brief overview of the mechanism of SERS technology and development of the SERS approach to detect bacterial pathogens in complex samples. The development of the label-based and label-free SERS strategies and several novel SERS-compatible technologies in clinical applications, as well as the analytical procedures and examples of chemometric methods for SERS, are introduced. The computational challenges of pre-processing spectra and the highlights of the limitations and perspectives of the SERS technique are also discussed.Taken together, this systematic review provides an overall summary of the SERS technique and its application potential for direct bacterial diagnosis in clinical samples such as blood, urine and sputum, etc.

Sensing of Antibiotic-Bacteria Interactions

Sensing of antibiotic-bacteria interactions is an important area of research that has gained significant attention in recent years. Antibiotic resistance is a major public health concern, and it is essential to develop new strategies for detecting and monitoring bacterial responses to antibiotics in order to maintain effective antibiotic development and antibacterial treatment. This review summarizes recent advances in sensing strategies for antibiotic-bacteria interactions, which are divided into two main parts: studies on the mechanism of action for sensitive bacteria and interrogation of the defense mechanisms for resistant ones. In conclusion, this review provides an overview of the present research landscape concerning antibiotic-bacteria interactions, emphasizing the potential for method adaptation and the integration of machine learning techniques in data analysis, which could potentially lead to a transformative impact on mechanistic studies within the field.

Establishing Compliance between Spectral, Colourimetric and Photometric Indicators in Resazurin Reduction Test

The resazurin reduction test is one of the basic tests for bacterial culture viability and drug resistance endorsed by the World Health Organisation. At the same time, conventional spectrophotometric and spectrofluorimetric methods demand rather bulky and expensive equipment. This induces a challenge for developing simpler approaches to sensor systems that are portable and applicable in resource-limited settings. In this work, we address two such alternative approaches, based on the colour processing of the microbiological plate's photographic images and single-channel photometry with a recently developed portable microbiological analyser. The key results consist of establishing a sequential linear correspondence between the concentration of resorufin produced due to the reduction of resazurin by viable bacteria as determined by the UV-Vis studies, the intensity of the a* channel of the CIE L*a*b* colour space and the transmitted light intensity registered by a luxmeter under the LED illumination with a yellow colour filter. This route is illustrated with the chemical system "Hydrazine hydrate - resazurin", isolating the target colour change-inducing reaction and the test of determining the minimal inhibition concentration of the antibacterial first-line drug isoniazid acting on the culture of the H37Rv strain of M. tuberculosis.

Role of Polysaccharides from Marine Seaweed as Feed Additives for Methane Mitigation in Ruminants: A Critical Review

Given the increasing concerns regarding greenhouse gas emissions associated with livestock production, the need to discover effective strategies to mitigate methane production in ruminants is clear. Marine algal polysaccharides have emerged as a promising research avenue because of their abundance and sustainability. Polysaccharides, such as alginate, laminaran, and fucoidan, which are extracted from marine seaweeds, have demonstrated the potential to reduce methane emissions by influencing the microbial populations in the rumen. This comprehensive review extensively examines the available literature and considers the effectiveness, challenges, and prospects of using marine seaweed polysaccharides as feed additives. The findings emphasise that marine algal polysaccharides can modulate rumen fermentation, promote the growth of beneficial microorganisms, and inhibit methanogenic archaea, ultimately leading to decreases in methane emissions. However, we must understand the long-term effects and address the obstacles to practical implementation. Further research is warranted to optimise dosage levels, evaluate potential effects on animal health, and assess economic feasibility. This critical review provides insights for researchers, policymakers, and industry stakeholders dedicated to advancing sustainable livestock production and methane mitigation.

Staphylococcus aureus - Review on potential targets for sensors development

Staphylococcus aureus (S. aureus) is accountable for a wide variety of clinical disease with a high rate of morbidity and mortality around the globe. It has a leading place into the ESKAPE group that includes six pathogens and exhibit multidrug resistance and are the major cause of healthcare associated infections: Enterococcus faecium, S. aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp. A critical overview regarding the development of sensors for both S. aureus and his, more dangerous alter ego, Methicillin-resistant S. aureus (MRSA) was presented focusing on the bacteria targets starting with the detection of the whole cell, up to specific wall components, toxins or other virulence factors. The literature data was systematically assessed having in sight the design of the sensing platforms, the analytical performances, and possible courses of action to be implemented in real practice as point-of-care (POC) devices. Moreover, a distinct section was dedicated to commercially available devices and out of the box approaches, namely the use of bacteriophages as an alternative to antimicrobial therapy and as sensors modifiers. The reviewed sensors and devices were discussed in terms of their suitability for different biosensing applications, in early screening of contamination regarding food analysis, environmental monitoring and in clinical diagnosis.

Development of europium(III) complex functionalized silica nanoprobe for luminescence detection of tetracycline

Increasing awareness of the health and environment impacts of the antibiotics misuse or overuse, such as tetracycline (TC) in treatment or prevention of infections and diseases, has driven the development of robust methods for their detection in biological, environmental and food systems. In this work, we report the development of a new europium(III) complex functionalized silica nanoprobe (SiNPs-Eu³⁺) for highly sensitive and selective detection of TC residue in aqueous solution and food samples (milk and meat). The nanoprobe is developed by immobilization of Eu³⁺ ion onto the surface of silica nanoparticles (SiNPs) as the emitter and TC recognition unit. The β-diketone configuration of TC can further coordinate with Eu³⁺ steadily on the surface of nanoprobe, facilitating the absorption of light excitation for Eu³⁺ emitter activation and luminescence "off-on" response. The dose-dependent luminescence enhancement of SiNPs-Eu³⁺ nanoprobe exhibits good linearities, allowing the quantitative detection of TC. The SiNPs-Eu³⁺ nanoprobe shows high sensitivity and selectivity for TC detection in buffer solution. Time resolved luminescence analysis enables the elimination of autofluorescence and light scattering for highly sensitive detection of TC in milk and pork mince with high accuracy and precision. The successful development of SiNPs-Eu³⁺ nanoprobe is anticipated to provide a rapid, economic, and robust approach for TC detection in real world samples.

High efficient electrochemical biosensor based on exonuclease-Ⅲ-assisted dual-recycling amplification for ultrasensitive detection of kanamycin

A target-triggered and exonuclease-Ⅲ-assisted strand displacement, dual-recycling amplification reaction-based biosensor was developed for the rapid, ultrasensitive and accurate detection of kanamycin. The robust profiling platform was constructed using high conductive MXene/VS₂ for the electrode surface modification and high active CeCu₂O₄ bimetallic nanoparticles as nanozyme to improve the sensitivity as well as the catalytic signal amplification of the biosensor. Using the dual supplementary recycling of primer DNA and hairpin DNA, the electrochemical platform could accurately detect kanamycin to as low as 0.6 pM from the range of 5 pM to 5 μM. By profiling five other antibiotics, this platform exhibited high specificity, enhanced repeatability and reproducibility. Based on these intrinsic characteristics and by utilizing milk and water samples, the as-designed biosensor offers a remarkable strategy for antibiotic detection due to its favorable analytical accuracy and reliability, thereby demonstrating potential application prospect for various antibiotic biosensing in food quality control, water contamination detection and biological safety analysis.

Electrokinetics in antimicrobial resistance analysis: A review

Infections caused by antimicrobial resistance are a serious problem in the world. Currently, commercial devices for antimicrobial susceptibility testing and resistant bacteria identification are time-consuming. There is an urgent need to develop fast and accurate methods, especially in the process of sample pretreatment. Electrokinetic (EK) is a family of electric-field-based kinetic phenomena of fluid or embedded objects, and EK applications have been found in various fields. In this paper, EK bacteria manipulation, including enrichment and separation, is reviewed. Focus is given to the rapid electric-based minimum inhibitory concentration measurement. The future directions and major challenges in this field are also outlined.

SERS-based antibiotic susceptibility testing: Towards point-of-care clinical diagnosis

Emerging antibiotic resistant bacteria constitute one of the biggest threats to public health. Surface-enhanced Raman scattering (SERS) is highly promising for detecting such bacteria and for antibiotic susceptibility testing (AST). SERS is fast, non-destructive (can probe living cells) and it is technologically flexible (readily integrated with robotics and machine learning algorithms). However, in order to integrate into efficient point-of-care (PoC) devices and to effectively replace the current culture-based methods, it needs to overcome the challenges of reliability, cost and complexity. Recently, significant progress has been made with the emergence of both new questions and new promising directions of research and technological development. This article brings together insights from several representative SERS-based AST studies and approaches oriented towards clinical PoC biosensing. It aims to serve as a reference source that can guide progress towards PoC routines for identifying antibiotic resistant pathogens. In turn, such identification would help to trace the origin of sporadic infections, in order to prevent outbreaks and to design effective medical treatment and preventive procedures.

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.

Detection and Quantification of Antimicrobial-Resistant Cells in Aquatic Environments by Bioorthogonal Noncanonical Amino Acid Tagging

Aquatic environments are important reservoirs of antibiotic wastes, antibiotic resistance genes, and bacteria, enabling the persistence and proliferation of antibiotic resistance in different bacterial populations. To prevent the spread of antibiotic resistance, effective approaches to detect antimicrobial susceptibility in aquatic environments are highly desired. In this work, we adopt a metabolism-based bioorthogonal noncanonical amino acid tagging (BONCAT) method to detect, visualize, and quantify active antimicrobial-resistant bacteria in water samples by exploiting the differences in bacterial metabolic responses to antibiotics. The BONCAT approach can be applied to rapidly detect bacterial resistance to multiple antibiotics within 20 min of incubation, regardless of whether they act on proteins or DNA. In addition, the combination of BONCAT with the microscope enables the intuitive characterization of antibiotic-resistant bacteria in mixed systems at single-cell resolution. Furthermore, BONCAT coupled with flow cytometry exhibits good performance in determining bacterial resistance ratios to chloramphenicol and population heterogeneity in hospital wastewater samples. In addition, this approach is also effective in detecting antibiotic-resistant bacteria in natural water samples. Therefore, such a simple, fast, and efficient BONCAT-based approach will be valuable in monitoring the increase and spread of antibiotic resistance within natural and engineered aquatic environments.

Ultrasensitive Fluorescence Lateral Flow Assay for Simultaneous Detection of Pseudomonas aeruginosa and Salmonella typhimurium via Wheat Germ Agglutinin-Functionalized Magnetic Quantum Dot Nanoprobe

Point-of-care testing methods for the rapid and sensitive screening of pathogenic bacteria are urgently needed because of the high number of outbreaks of microbial infections and foodborne diseases. In this study, we developed a highly sensitive and multiplex lateral flow assay (LFA) for the simultaneous detection of Pseudomonas aeruginosa and Salmonella typhimurium in complex samples by using wheat germ agglutinin (WGA)-modified magnetic quantum dots (Mag@QDs) as a universal detection nanoprobe. The Mag@QDs-WGA tag with a 200 nm Fe3O4 core and multiple QD-formed shell was introduced into the LFA biosensor for the universal capture of the two target bacteria and provided the dual amplification effect of fluorescence enhancement and magnetic enrichment for ultra-sensitivity detection. Meanwhile, two antibacterial antibodies were separately sprayed onto the two test lines of the LFA strip to ensure the specific identification of P. aeruginosa and S. typhimurium through one test. The proposed LFA exhibited excellent analytical performance, including high capture rate (>80%) to the target pathogens, low detection limit (<30 cells/mL), short testing time (<35 min), and good reproducibility (relative standard deviation < 10.4%). Given these merits, the Mag@QDs-WGA-based LFA has a great potential for the on-site and real-time diagnosis of bacterial samples.

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

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

Electrochemical Quantification of Tobramycin Retention in Pseudomonas aeruginosa as Antimicrobial Susceptibility Indicator

The emergence and spread of bacterial resistance to antibiotics has developed into one of the most challenging threats to public health. Antibiotic susceptibility tests (ASTs) for bacterial infections are now essential, because they provide guidance for physicians in the selection of antibiotics, to which bacteria will respond. Most current AST methods require long periods of time, because of bacterial growth and incubation, leading to a prolonged and overuse of broad-spectrum antibiotics. Thus, there is a growing demand for methods and technologies that enable rapid antibiotic susceptibility assessment. Due to advantages related to cost-effectiveness, rapid response time and high sensitivity, electrochemical detection methods are promising analytical tools that can successfully quantify antibiotic uptake and retention in clinically relevant bacterial strains. This study presents the electroanalytical quantification of tobramycin (TOB) retention in susceptible and resistant bacterial strains of Pseudomonas aeruginosa. The electrochemical behavior of TOB was characterized by voltammetry, identifying redox potentials, the current dependence on pH conditions, and the detection limit at unmodified glassy carbon electrodes. The presented methodology was able to distinguish between susceptible and resistant bacterial strains, and is also capable of identifying varying degrees of resistance against TOB. The presented approach detects the immediate interaction of bacteria with an antibiotic, without the need of complex and cost-intense equipment related to genomic testing methods.

Ultrasensitive multichannel immunochromatographic assay for rapid detection of foodborne bacteria based on two-dimensional film-like SERS labels

Rapid and sensitive detection of multiple foodborne bacteria without DNA amplification is still challenging. Here, we proposed an immunochromatographic assay (ICA) with multiplex analysis ability and high sensitivity for direct detection of bacteria in real food samples, based on an improved surface-enhanced Raman scattering (SERS) sensing strategy. Multifunctional Au shell-coated graphene oxide nanosheets (GO@Au) were fabricated and for the first time introduced into the ICA system as a two-dimensional film-like SERS label, which possessed huge surface area, excellent stability, and superior SERS activity. Different from the conventional spherical nanotags, the antibody-conjugated GO@Au nanosheet effectively and rapidly adhered to bacterial cells, improved the dispersibility of bacteria-nanolabel complexes on the ICA strips, and provided numerous stable hotspots for SERS signal enhancement. The combination of GO@Au labels and the ICA system achieved the multiplex and ultrasensitive determination of three major foodborne pathogens, namely, Staphylococcus aureus, Escherichia coli O157:H7, and Salmonella typhimurium, in a single test, with low detection limits (8, 10, and 10 cells/mL) and short detection time (20 min). The proposed biosensor demonstrated high stability and good accuracy in various food samples and is thus a promising tool for the rapid identification of bacteria.

Medicinal Chemistry of Inhibitors Targeting Resistant Bacteria

The discovery of antibiotics was a revolutionary feat that provided countless health benefits. The identification of penicillin by Alexander Fleming initiated the era of antibiotics, represented by constant discoveries that enabled effective treatments for the different classes of diseases caused by bacteria. However, the indiscriminate use of these drugs allowed the emergence of resistance mechanisms of these microorganisms against the available drugs. In addition, the constant discoveries in the 20th century generated a shortage of new molecules, worrying health agencies and professionals about the appearance of multidrug-resistant strains against available drugs. In this context, the advances of recent years in molecular biology and microbiology have allowed new perspectives in drug design and development, using the findings related to the mechanisms of bacterial resistance to generate new drugs that are not affected by such mechanisms and supply new molecules to be used to treat resistant bacterial infections. Besides, a promising strategy against bacterial resistance is the combination of drugs through adjuvants, providing new expectations in designing new antibiotics and new antimicrobial therapies. Thus, this manuscript will address the main mechanisms of bacterial resistance under the understanding of medicinal chemistry, showing the main active compounds against efflux mechanisms, and also the application of the use of drug delivery systems, and finally, the main potential natural products as adjuvants or with promising activity against resistant strains.

Compound Raman microscopy for rapid diagnosis and antimicrobial susceptibility testing of pathogenic bacteria in urine

Rapid identification and antimicrobial susceptibility testing (AST) of bacteria are key interventions to curb the spread and emergence of antimicrobial resistance. The current gold standard identification and AST methods provide comprehensive diagnostic information but often take 3 to 5 days. Here, a compound Raman microscopy (CRM), which integrates Raman spectroscopy and stimulated Raman scattering microscopy in one system, is presented and demonstrated for rapid identification and AST of pathogens in urine. We generated an extensive bacterial Raman spectral dataset and applied deep learning to identify common clinical bacterial pathogens. In addition, we employed stimulated Raman scattering microscopy to quantify bacterial metabolic activity to determine their antimicrobial susceptibility. For proof-of-concept, we demonstrated an integrated assay to diagnose urinary tract infection pathogens, S. aureus and E. coli. Notably, the CRM system has the unique ability to provide Gram-staining classification and AST results within ~3 h directly from urine samples and shows great potential for clinical applications.

Electrogenic Bacteria Promise New Opportunities for Powering, Sensing, and Synthesizing

Considerable research efforts into the promises of electrogenic bacteria and the commercial opportunities they present are attempting to identify potential feasible applications. Metabolic electrons from the bacteria enable electricity generation sufficient to power portable or small-scale applications, while the quantifiable electric signal in a miniaturized device platform can be sensitive enough to monitor and respond to changes in environmental conditions. Nanomaterials produced by the electrogenic bacteria can offer an innovative bottom-up biosynthetic approach to synergize bacterial electron transfer and create an effective coupling at the cell-electrode interface. Furthermore, electrogenic bacteria can revolutionize the field of bioelectronics by effectively interfacing electronics with microbes through extracellular electron transfer. Here, these new directions for the electrogenic bacteria and their recent integration with micro- and nanosystems are comprehensively discussed with specific attention toward distinct applications in the field of powering, sensing, and synthesizing. Furthermore, challenges of individual applications and strategies toward potential solutions are provided to offer valuable guidelines for practical implementation. Finally, the perspective and view on how the use of electrogenic bacteria can hold immeasurable promise for the development of future electronics and their applications are presented.

A Review of Raman-Based Technologies for Bacterial Identification and Antimicrobial Susceptibility Testing

Antimicrobial resistance (AMR) is a global medical threat that seriously endangers human health. Rapid bacterial identification and antimicrobial susceptibility testing (AST) are key interventions to combat the spread and emergence of AMR. Although current clinical bacterial identification and AST provide comprehensive information, they are labor-intensive, complex, inaccurate, and slow (requiring several days, depending on the growth of pathogenic bacteria). Recently, Raman-based identification and AST technologies have played an increasingly important role in fighting AMR. This review summarizes major Raman-based techniques for bacterial identification and AST, including spontaneous Raman scattering, surface-enhanced Raman scattering (SERS), and coherent Raman scattering (CRS) imaging. Then, we discuss recent developments in rapid identification and AST methods based on Raman technology. Finally, we highlight the major challenges and potential future efforts to improve clinical outcomes through rapid bacterial identification and AST.

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.

RamanNet: a lightweight convolutional neural network for bacterial identification based on Raman spectra

Raman spectroscopy combined convolutional neural network (CNN) enables rapid and accurate identification of the species of bacteria. However, the existing CNN requires a complex hyperparameters model design. Herein, we propose a new simple network architecture with less hyperparameter design and low computation cost, RamanNet, for rapid and accurate identifying of bacteria at the species level based on its Raman spectra. We verified that compared with the previous CNN methods, the RamanNet reached comparable results on the Bacteria-ID Raman spectral dataset and PKU-bacterial Raman spectral datasets, but using only about 1/45 and 1/297 network parameters, respectively. RamanNet achieved an average isolate-level accuracy of 84.7 ± 0.3%, antibiotic treatment identification accuracy of 97.1 ± 0.3%, and distinguished accuracy of 81.6 ± 0.9% for methicillin-resistant and -susceptible Staphylococcus aureus (MRSA and MSSA) on the Bacteria-ID dataset, respectively. Moreover, it achieved an average accuracy of 96.04% on the PKU-bacterial dataset. The RamanNet model benefited from fewer model parameters that can be quickly trained even using CPU. Therefore, our method has the potential to rapidly and accurately identify bacterial species based on their Raman spectra and can be easily extended to other classification tasks based on Raman spectra.

We propose a novel CNN model named RamanNet for rapid and accurate identification of bacteria at the species-level based on Raman spectra. Compared to previous CNN methods, the RamanNet reached comparable results on the Bacteria-ID Raman spectral dataset.

Universal and ultrasensitive detection of foodborne bacteria on a lateral flow assay strip by using wheat germ agglutinin-modified magnetic SERS nanotags

Rapid, direct and sensitive detection of foodborne bacteria in complex samples is still challenging. Here, we reported a universal surface-enhanced Raman scattering (SERS)-based lateral flow assay (LFA) for highly sensitive detection of foodborne bacteria in food and environmental samples using wheat germ agglutinin (WGA)-modified Fe₃O₄@Au (Au@MNP-WGA) nanotags. The Au@MNP-WGA tag with numerous intraparticle hotspots was integrated into the LFA system for the first time, which can not only greatly improve the detection sensitivity through the dual amplification effect of magnetic enrichment and SERS enhancement but also achieve the broad-spectrum capture of multiple bacteria. In addition, monoclonal antibodies were separately immobilized onto the test line of different LFA strips to ensure the specific detection of different target pathogens. With this strategy, the proposed assay can achieve the universal and highly sensitive determination of three common foodborne bacteria, namely, Listeria monocytogenes, Campylobacter jejuni, and Staphylococcus aureus, with low detection limit (10 cells mL⁻¹), short testing time (<35 min), and high reproducibility (RSD < 8.14%). Given its good stability and accuracy in complex samples, the Au@MNP-WGA-based SERS-LFA has great potential to be a powerful tool for the universal and on-site detection of different foodborne pathogens.

A universal SERS-based lateral flow assay was proposed for highly sensitive detection of foodborne bacteria in food and environmental samples using wheat germ agglutinin-modified Fe₃O₄@Au nanotags.

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

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

An efficient SERS platform for the ultrasensitive detection of Staphylococcus aureus and Listeria monocytogenes via wheat germ agglutinin-modified magnetic SERS substrate and streptavidin/aptamer co-functionalized SERS tags

A novel surface-enhanced Raman scattering (SERS)-based analytical technique was proposed to simultaneously detect two highly pathogenic bacteria, namely, Staphylococcus aureus (S. aureus) and Listeria monocytogenes (L. mono) by using a dual-recognition pattern with wheat germ agglutinin (WGA) and nucleic acid aptamers. WGA was modified onto Fe₃O₄@Au magnetic nanoparticles (MNPs) for the efficient capture of S. aureus and L. mono in complex samples (orange juice, extracts of lettuce, and human urine) within 15 min. The streptavidin (SA)/aptamers co-functionalized SERS tags were fabricated by covalent attaching two different Raman reporters and SA molecules onto 45 nm Au NPs and then conjugated with two biotin-aptamers that specifically bind to their target bacteria with high affinity and stability. The combined use of high-sensitive SERS tags, WGA-mediated magnetic enrichment, and SA-mediated aptamer conjugation remarkably improved the assay sensitivity. Under optimized conditions, the developed SERS biosensor can simultaneously detect the two target bacteria with high detection sensitivity (<6 cells/mL), favorable linear relation (10-10⁷ cells/mL), and high accuracy (recovery rate <7.03%). Therefore, the proposed SERS platform is rapid, sensitive, easy to use, and thus show potential as a tool for the timely identification of pathogenic bacteria in real samples.

Electrochromogenic Detection of Live Bacteria Using Soluble and Insoluble Prussian Blue

Microbial detection is crucial for the control and prevention of infectious diseases, being one of the leading causes of mortality worldwide. Among the techniques developed for bacterial detection, those based on metabolic indicators are progressively gaining interest due to their simplicity, adaptability, and, most importantly, their capacity to differentiate between live and dead bacteria. Prussian blue (PB) may act as a metabolic indicator, being reduced by bacterial metabolism, producing a visible color change from blue to colorless. This molecule can be present in two main forms, namely, the soluble and the insoluble, having different properties and structures. In the current work, the bacterial-sensing capacity of soluble and insoluble PB will be tested and compared both in suspensions as PB-NPs and after deposition on transparent indium tin oxide-poly(ethylene terephthalate) (ITO-PET) electrodes. In the presence of live bacteria, PB-NPs are metabolized and completely reduced to the Prussian white state in less than 10 h for soluble and insoluble forms. However, when electrodeposited on ITO-PET substrates, less than 1 h of incubation with bacteria is required for both forms, although the soluble one presents faster metabolic reduction kinetics. This study paves the way to the use of Prussian blue as a metabolic indicator for the early detection of bacterial infection in fields like microbial diagnostics, surface sterilization, food and beverage contamination, and environmental pollution, among others.

Scale-adaptive Deep Model for Bacterial Raman Spectra Identification

The combination of Raman spectroscopy and deep learning technology provides an automatic, rapid, and accurate scheme for the clinical diagnosis of pathogenic bacteria. However, the accuracy of existing deep learning methods is still limited because of the single and fixed scales of deep neural networks. We propose a deep neural network that can learn multi-scale features of Raman spectra by using the automatic combination of multi-receptive fields of convolutional layers. This model is based on the expert knowledge that the discrimination information of Raman spectra is composed of multi-scale spectral peaks. We enhance the interpretability of the model by visualizing the activated wavenumbers of the bacterial spectrum that can be used for reference in related work. Compared with existing state-of-the-art methods, the proposed method achieves higher accuracy and efficiency for bacterial identification on isolate-level, empiric-treatment-level, and antibiotic-resistance-level tasks. The clinical bacterial identification task requires significantly fewer patient samples to achieve similar accuracy. Therefore, this method has tremendous potential for the identification of clinical pathogenic bacteria, antibiotic susceptibility testing, and prescription guidance.

Antimicrobial susceptibility testing by measuring bacterial oxygen consumption on an integrated platform

Cellular respiration is a fundamental feature of metabolic activity and oxygen consumption can be considered as a reliable indicator of bacterial aerobic respiration, including for facultative anaerobic bacteria like E. coli. Addressing the emerging global health challenge of antimicrobial resistance, we performed antimicrobial susceptibility testing using the bacterial oxygen consumption rate (OCR) as a phenotypic indicator. We demonstrated that microbial exposure to antibiotics showed systematic OCR variations, which enabled determining minimum inhibitory concentrations for three clinically relevant antibiotics, ampicillin, ciprofloxacin, and gentamicin, within a few hours. Our study was performed by using photoluminescence-based oxygen sensing in a microchamber format, which enabled reducing the sample volume to a few hundred microliters. OCR modeling based on exponential bacterial growth allowed estimating the bacterial doubling time for various culture conditions (different types of media, different culture temperature and antibiotic concentrations). Furthermore, correlating metabolic heat production data, as obtained by nanocalorimetry in the same type of microchamber, and OCR measurements provided further insight on the actual metabolic state and activity of a microbial sample. This approach represents a new path towards more comprehensive microbiological studies performed on integrated miniaturized systems.

BactoSpin: Novel Technology for Rapid Bacteria Detection and Antibiotic Susceptibility Testing

Inappropriate use of antibiotics is one of the leading causes of the increasing numbers of resistant bacteria strains, resulting in 700,000 deaths worldwide each year. Reducing unnecessary use of antibiotics and choosing the most effective antibiotics instead of broad-spectrum drugs will slow the arms race between germs and humans. Urinary tract infections (UTIs) are among the most common bacterial infections. Currently, accurate diagnosis of UTI requires approximately 48 h from the time of urine sample collection until antibiotic susceptibility test (AST) results. This work presents a rapid bacterial detection device that integrates a centrifuge, microscope, and incubator. Two disposable microfluidic chips were developed. The first chip was designed for bacteria concentration, detection, and medium exchange. A second multi-channel chip was developed for AST. This chip contains superhydrophobic and hydrophilic coatings to ensure liquid separation between the channels without the need for valves. The designed chips supported the detection of E. coli at a concentration as low as 5 × 10³ cells/mL within 5 min and AST in under 2 h. AST was also successfully performed with Klebsiella pneumonia isolated from a human urine sample. In addition, machine-learning-based image recognition was shown to reduce the required time for AST and to provide results within 1 h for E. coli cells. Thus, the BactoSpin device can serve as an efficient and rapid platform for UTI diagnostics and AST.

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.

Recent developments in Raman spectral analysis of microbial single cells: Techniques and applications

The conventional microbial cell analyses are mostly population-averaged methods that conceal the characteristics of single-cell in the community. Single-cell analysis can provide information on the functional and structural variation of each cell, resulting in the elimination of long and tedious microbial cultivation techniques. Raman spectroscopy is a label-free, noninvasive, and in-vivo method ideal for single-cell measurement to obtain spatially resolved chemical information. In the current review, recent developments in Raman spectroscopic techniques for microbial characterization at the single-cell level are presented, focusing on Raman imaging of single cells to study the intracellular distribution of different components. The review also discusses the limitation and challenges of each technique and put forward some future outlook for improving Raman spectroscopy-based techniques for single-cell analysis. Raman spectroscopic methods at the single-cell level have potential in precision measurements, metabolic analysis, antibiotic susceptibility testing, resuscitation capability, and correlating phenotypic information to genomics for cells, the integration of Raman spectroscopy with other techniques such as microfluidics, stable isotope probing (SIP), and atomic force microscope can further improve the resolution and provide extensive information. Future focuses should be given to advance algorithms for data analysis, standardized reference libraries, and automated cell isolation techniques in future.

Rapid antimicrobial susceptibility testing by stimulated Raman scattering metabolic imaging and morphological deformation of bacteria

Methods for rapid antimicrobial susceptibility testing (AST) are urgently needed to address the emergence and spread of antimicrobial resistance. Here, we report a new method based on stimulated Raman scattering (SRS) microscopy, which measures both the metabolic activity and the morphological deformation of bacteria to determine the antimicrobial susceptibility of β-lactam antibiotics rapidly. In this approach, we quantify single bacteria's metabolic activity by the carbon-deuterium (C-D) bond concentrations in bacteria after D₂O incubation. In the meantime, bacterial morphological deformation caused by β-lactam antibiotics is also measured. With these two quantifiable markers, we develop an evaluation method to perform AST of cefotaxime on 103 E. coli strains. Our method achieved a 93.2% categorical agreement and a 93.2% essential agreement with the standard reference method.

DEPIS: A combined dielectrophoresis and impedance spectroscopy platform for rapid cell viability and antimicrobial susceptibility analysis

Antimicrobial resistance (AMR) is caused by inappropriate or excessive antibiotic consumption. Early diagnosis of bacterial infections can greatly curb empirical treatment and thus AMR. Current diagnostic procedures are time-consuming as they rely on gene amplification and cell culture techniques that are inherently limited by the doubling rate of the involved species. Further, biochemical methods for species identification and antibiotic susceptibility testing for drug/dose effectiveness take several days and are non-scalable. We report a real-time, label-free approach called DEPIS that combines dielectrophoresis (DEP) for bacterial enrichment and impedance spectroscopy (IS) for cell viability analysis under 60 min. Target bacteria are captured on interdigitated electrodes using DEP (30 min) and their antibiotic-induced stress response is measured using IS (another 30 min). This principle is used to generate minimum bactericidal concentration (MBC) plots by measuring impedance change due to ionic release by dying bacteria in a low conductivity buffer. The results are rapid since they rely on cell death rather than cell growth which is an intrinsically slower process. The results are also highly specific and work across all bactericidal antibiotics studied, irrespective of their cellular target or drug action mechanism. More importantly, preliminary results with clinical isolates show that methicillin-susceptible Staphylococcus aureus (MSSA) can easily be differentiated from methicillin-resistant S. aureus (MRSA) under 1 h. This rapid cell analyses approach can aid in faster diagnosis of bacterial infections and benefit the clinical decision-making process for antibiotic treatment, addressing the critical issue of AMR.

Identification of carbapenems resistant genes on biofilm forming K. pneumoniae from urinary tract infection

The multi-drug resistant effect of the Gram negative bacteria K. pneumoniae was identified by disc diffusion method using specific UTI panel discs of Kleb 1 HX077 and Kleb 2 HX090 HEXA. Among the multi-drug resistant bacteria, the carbapenem resistant (CR) effect of the K. pneumoniae was screened by specific carbapenem detection antibiotics of HEXA HX066 and HX0103 HEXA by disc diffusion method. In addition, the effective antibiotics were further performed against K. pneumoniae by minimum inhibition concentration method. Further, the carbapenemase genes of VIM 1 and IMP 1 were detected from the isolated strains by multiplex PCR method. Furthermore, the biofilm forming ability of selected carbapenem resistant K. pneumoniae was initially identified by tissue culture plate method and confirmed by exopolysaccharide arrest ability of congo red agar assay. Finally, our result was proved that the identified K. pneumoniae is carbapenemase producing strain, and its virulence was extended with strong biofilm formation.

Pathogen detection with electrochemical biosensors: Advantages, challenges and future perspectives

Detection of pathogens, e.g., bacteria and viruses, is still a big challenge in analytical medicine due to their vast number and variety. Developing strategies for rapid, inexpensive, specific, and sensitive detection of the pathogens using nanomaterials, integrating with microfluidics devices, amplification methods, or even combining these strategies have received significant attention. Especially, after the health-threatening COVID-19 outbreak, rapid and sensitive detection of pathogens became very critical. Detection of pathogens could be realized with electrochemical, optical, mass sensitive, or thermal methods. Among them, electrochemical methods are very promising by bringing different advantages, i.e., they exhibit more versatile detection schemes and real-time quantification as well as label-free measurements, which provides a broader application perspective. In this review, we discuss the recent advances for the detection of bacteria and viruses using electrochemical biosensors. Moreover, electrochemical biosensors for pathogen detection were broadly reviewed in terms of analyte, bio-recognition and transduction elements. Different fabrication techniques, detection principles, and applications of various pathogens with the electrochemical biosensors were also discussed.

Biofilm formation and extracellular microvesicles-The way of foodborne pathogens toward resistance

Almost all known foodborne pathogens are able to form biofilms as one of the strategies for survival under harsh living conditions, to ward off the inhibition and the disinfection during food production, transport and storage, as well as during cleaning and sanitation of corresponding facilities. Biofilms are communities where microbial cells live under constant intracellular interaction and communication. Members of the biofilm community are embedded into extracellular matrix that contains polysaccharides, DNA, lipids, proteins, and small molecules that protect microorganisms and enable their intercellular communication under stress conditions. Membrane vesicles (MVs) are produced by both Gram positive and Gram negative bacteria. These lipid membrane-enveloped nanoparticles play an important role in biofilm genesis and in communication between different biofilm members. Furthermore, MVs are involved in other important steps of bacterial life like cell wall modeling, cellular division, and intercellular communication. They also carry toxins and virulence factors, as well as nucleic acids and different metabolites, and play a key role in host infections. After entering host cells, MVs can start many pathologic processes and cause serious harm and cell death. Prevention and inhibition of both biofilm formation and shedding of MVs by foodborne pathogens has a very important role in food production, storage, and food safety in general. Better knowledge of biofilm formation and maintaining, as well as the role of microbial vesicles in this process and in the process of host cells' infection is essential for food safety and prevention of both food spoilage and host infection.