Bacterial identification and adhesive strength evaluation based on a mannose biosensor with dual-mode detection

Diagnosis Accuracy of Raman Spectroscopy in the Identification of Pathogenic Bacteria

As an emerging technology, Raman spectroscopy (RS) has been used to identify pathogenic bacteria with excellent performance. The aim of this study was to verify the diagnosis accuracy of RS in identification of pathogenic bacteria. This meta-analysis systematically evaluated the accuracy of RS for identification of pathogenic bacteria. We searched the electronic databases of PubMed and Web of Science to obtain relevant articles; STATA 15.1 was used to analyze all sensitivities, specificies, and their 95% confidence interval (CI). The summary receiver operating characteristic curves (SROC) and area under the curve (AUC) were used to display more performance of RS. Nineteen articles were included according to the inclusion and exclusion criteria. The pooled sensitivity and specificity of RS for the identification of pathogenic bacteria were 0.94 (95% CI, 0.89-0.96) and 0.99 (95% CI, 0.97-0.99). The diagnostic odds ratio (DOR) was 1209 (95% CI, 367-3980), and AUC of SROC was 0.99 (95% CI, 0.98-1.00). For gram-positive bacteria, the sensitivity and specificity of different species ranged from 0.00 to 1.00 and 0.96 to 1.00, with a pooled sensitivity and specificity of 0.96 (95% CI, 0.90-0.98) and 0.99 (95% CI, 0.98-1.00). For gram-negative bacteria, the sensitivity and specificity of different species ranged from 0.30 to 1.00 and 0.92 to 1.00, with a pooled sensitivity and specificity of 0.92 (95% CI, 0.76-0.98) and 0.99 (95% CI, 0.98-1.00). For acid-fast bacteria, the sensitivity and specificity of different species ranged from 0.83 to 1.00 and 0.96 to 1.00, with a pooled sensitivity and specificity of 0.96 (95% CI, 0.84-0.99) and 1.00 (95% CI, 0.96-1.00). RS provides a new method for pathogenic bacteria identification and demonstrates high sensitivity and specificity for most included species.

Multivalent acetylated-sialic acid as recognition elements for the electrochemical sensing of viral antigens

Electrochemical biosensors hold great promise for the rapid screening of viral infectious diseases. However, the recognition elements of these biosensors are typically limited to antibodies, aptamers, and molecularly imprinted polymers. In this study, acetylated sialic acids were explored as recognition elements because they serve as natural viral receptors expressed on host cells. Specifically, 4-O-acetylated-SA (4-O-Ac-SA) and 9-O-Ac-SA, were synthesized selectively, and their binding affinity with the SARS-CoV-2 S antigen was examined. The S antigen tended to bind to 9-O-Ac-SA. Additionally, the biocompatibility and neutralizing effects of 4/9-O-Ac-SA on the S antigen were validated. The validation demonstrated that 9-O-Ac-SA could efficiently inhibit S antigen binding to host cells. The cluster glycoside effect of the recognition between the S antigen and 9-O-Ac-SA was validated. Subsequently, an electrochemical biosensor for the rapid screening of viral antigens was developed using 9-O-Ac-SA as the recognition element. The application of electrochemical impedance spectroscopy as a readout method allowed for the identification of the S antigen at concentrations of 10 ng/mL with acceptable stability and repeatability. The biosensor demonstrated a strong linear response over the range of 10∼1 × 104 ng/mL. In summary, the study presented a promising recognition element for the development of electrochemical biosensors for rapid viral infection screening. The utilization of glycans for viral antigen detection could pave the way for innovative advances in electrochemical biosensor technology.

Agglutination of Escherichia coli, Clostridium perfringens, and Salmonella enterica through competitive exclusion using potassium chloride with gum arabic

Bacterial infections causing necrotic enteritis and diarrhea pose a considerable economic loss to the animal industry. Using mannose oligosaccharides as competitive exclusion agents is an alternative method to antibiotic growth promoters; however, these materials are rapidly metabolized by gut microbiota, posing a challenge in sustaining their efficacy. The aim of this study was to identify an agglutination material that is effective against pathogens. Polysaccharides and salts were assessed using agglutination assays, microscopy, and zeta potential analysis. Gum arabic (GA) demonstrated strong agglutination against Escherichia coli and Salmonella enterica. Potassium chloride altered the cell form of Clostridium perfringens from rod-like to coccoid. When combined with GA, KCl effectively agglutinated all three bacterial species tested. Zeta potential analysis showed that agglutination resulted from bacteria, GA, and KCl interactions. Among various salts mixed with GA, KCl was found to strongly agglutinate C. perfringens upon its change into the coccoid form. Moreover, this combination has been shown to agglutinate mixtures of pathogens, such as C. perfringens and S. enterica. Thus, a combination of GA and KCl offers a potential solution to combat the pathogens associated with necrotic enteritis and diarrhea in animals.

A pump-free paper/PDMS hybrid microfluidic chip for bacteria enrichment and fast detection

Developing portable and sensitive biosensors for bacteria detection is highly demanded due to their association with environmental and food safety. Paper-based microfluidic chip is the suitable candidate for constructing pump-free biosensor since paper is hydrophilic, low-cost and easy to use. However, the contradiction between sensitivity and small sample volume seriously affects the application of paper-based chip for bacteria detection. Here, a new microfluidic biosensor, combining large PDMS reservoir for sample storage, hydrophilic paper substrate for pump-free water transport, coated microspheres for bacteria capture and super absorbent resin for water absorption, is designed for the detection of bacteria in aqueous samples. Once the sample solution is introduced in the reservoir, water will automatically flow through the gaps between microspheres and the target bacteria will be captured by the aptamer coated on the surface. To facilitate PDMS reservoir bonding and ensure water transport, the upper side of paper substrate is coated with Polyethylenimine modified PDMS and the bottom side is kept unchanged. After all the solution is filtrated, fluorescent dye strained bacteria are enriched on the microspheres. The fluorescent intensity representing the number of bacteria captured is then measured using a portable instrument. Through the designed microfluidic biosensor, the bacteria detection can be achieved with 2 mL sample solution in less than 15 min for water or 20 min for diluted milk. A linear range from 10 CFU/mL to 1000 CFU/mL is obtained. The paper-based 3D biosensor has the merits of low-cost, simple operation, pump-free and high sensitivity and it can be applied to the simultaneous detection of multiple bacteria via integrating different aptamers.

A generalizable sensing platform based on molecularly imprinted polymer-aptamer double recognition and nanoenzyme assisted photoelectrochemical-colorimetric dual-mode detection

Developing highly sensitive and selective methods that incorporate specific recognition elements is crucial for detecting small molecules because of the limited availability of small molecule antibodies and the challenges in obtaining sensitive signals. In this study, a generalizable photoelectrochemical-colorimetric dual-mode sensing platform was constructed based on the synergistic effects of a molecularly imprinted polymer (MIP)-aptamer sandwich structure and nanoenzymes. The MIP functionalized peroxidase-like Fe3O4 (Fe3O4@MIPs) and alkaline phosphatase mimic Zr-MOF labeled aptamer (Zr-mof@Apt) were used as the recognition elements. By selectively accumulating dibutyl phthalate (DBP), a small molecule target model, on Fe3O4@MIPs, the formation of Zr-MOF@Apt-DBP- Fe3O4@MIPs sandwich structure was triggered. Fe3O4@MIPs oxidized TMB to form blue-colored oxTMB. However, upon selective accumulation of DBP, the catalytic activity of Fe3O4@MIPs was inhibited, resulting in a lighter color that was detectable by the colorimetric method. Additionally, Zr-mof@Apt effectively catalyzed the hydrolysis of L-Ascorbic acid 2-phosphate sesquimagnesium salt hydrate (AAPS), generating ascorbic acid (AA) that could neutralize the photogenerated holes to decrease the photocurrent signals for PEC sensing and reduce oxTMB for colorimetric testing. The dual-mode platform showed strong linearity for different concentrations of DBP from 1.0 pM to 10 μM (PEC) and 0.1 nM to 0.5 μM (colorimetry). The detection limits were 0.263 nM (PEC) and 30.1 nM (colorimetry) (S/N = 3), respectively. The integration of dual-signal measurement mode and sandwich recognition strategy provided a sensitive and accurate platform for the detection of small molecules.

Key steps for improving bacterial SERS signals in complex samples: Separation, recognition, detection, and analysis

Rapid and reliable detection of pathogenic bacteria is absolutely essential for research in environmental science, food quality, and medical diagnostics. Surface-enhanced Raman spectroscopy (SERS), as an emerging spectroscopic technique, has the advantages of high sensitivity, good selectivity, rapid detection speed, and portable operation, which has been broadly used in the detection of pathogenic bacteria in different kinds of complex samples. However, the SERS detection method is also challenging in dealing with the detection difficulties of bacterial samples in complex matrices, such as interference from complex matrices, confusion of similar bacteria, and complexity of data processing. Therefore, researchers have developed some technologies to assist in SERS detection of bacteria, including both the front-end process of obtaining bacterial sample data and the back-end data processing process. The review summarizes the key steps for improving bacterial SERS signals in complex samples: separation, recognition, detection, and analysis, highlighting the principles of each step and the key roles for SERS pathogenic bacteria analysis, and the interconnectivity between each step. In addition, the current challenges in the practical application of SERS technology and the development trends are discussed. The purpose of this review is to deepen researchers' understanding of the various stages of using SERS technology to detect bacteria in complex sample matrices, and help them find new breakthroughs in different stages to facilitate the detection and control of bacteria in complex samples.

PEC-SERS Dual-Mode Detection of Foodborne Pathogens Based on Binding-Induced DNA Walker and C3N4/MXene-Au NPs Accelerator

In this paper, a photoelectrochemical (PEC)-surface-enhanced Raman scattering (SERS) dual-mode biosensor is constructed coupled with a dual-recognition binding-induced DNA walker with a carbon nitride nanosheet (C3N4)/MXene-gold nanoparticles (C/M-Au NPs) accelerator, which is reliable and capable for sensitive and accurate detection of Staphylococcus aureus (S. aureus). Initially, a photoactive heterostructure is formed by combining C3N4 and MXene via a simple electrostatic self-assembly as they possess well-matched band-edge energy levels. Subsequently, in situ growth of gold nanoparticles on the formed surface results in better PEC performance and SERS activity, because of the synergistic effects of surface plasmon resonance and Schottky barrier. Furthermore, a three-dimensional, bipedal, and dual-recognition binding-induced DNA walker is introduced with the formation of Pb2+-dependent DNAzyme. In the presence of S. aureus, a significant quantity of intermediate DNA (I-DNA) is generated, which can open the hairpin structure of Methylene Blue-tagged hairpin DNA (H-MB) on the electrode surface, thereby enabling the switch of signals for the quantitative determination of S. aureus. The constructed PEC-SERS dual-mode biosensor that can be mutually verified under one reaction effectively addresses the problem of the low detection accuracy of traditional sensors. Experimental results revealed that the effective combination of PEC and SERS is achieved for amplification detection of S. aureus with a detection range of 5-108 CFU/mL (PEC) and 10-108 CFU/mL (SERS), and a detection of limit of 0.70 CFU/mL (PEC) and 1.35 CFU/mL (SERS), respectively. Therefore, this study offers a novel and effective dual-mode sensing strategy, which has important implications for bioanalysis and health monitoring.

Unraveling surface-enhanced Raman spectroscopy results through chemometrics and machine learning: principles, progress, and trends

Surface-enhanced Raman spectroscopy (SERS) has gained increasing attention because it provides rich chemical information and high sensitivity, being applicable in many scientific fields including medical diagnosis, forensic analysis, food control, and microbiology. Although SERS is often limited by the lack of selectivity in the analysis of samples with complex matrices, the use of multivariate statistics and mathematical tools has been demonstrated to be an efficient strategy to circumvent this issue. Importantly, since the rapid development of artificial intelligence has been promoting the implementation of a wide variety of advanced multivariate methods in SERS, a discussion about the extent of their synergy and possible standardization becomes necessary. This critical review comprises the principles, advantages, and limitations of coupling SERS with chemometrics and machine learning for both qualitative and quantitative analytical applications. Recent advances and trends in combining SERS with uncommonly used but powerful data analysis tools are also discussed. Finally, a section on benchmarking and tips for selecting the suitable chemometric/machine learning method is included. We believe this will help to move SERS from an alternative detection strategy to a general analytical technique for real-life applications.

Advances in surface-enhanced Raman spectroscopy technology for detection of foodborne pathogens

Rapid control and prevention of diseases caused by foodborne pathogens is one of the existing food safety regulatory issues faced by various countries and has received wide attention from all sectors of society. The development of rapid and reliable detection methods for foodborne pathogens remains a hot research area for food safety and public health because of the limitations of complex steps, time-consuming, low sensitivity, or poor selectivity of commonly used methods. Surface-enhanced Raman spectroscopy (SERS), as a novel spectroscopic technique, has the advantages of high sensitivity, selectivity, rapid and nondestructive detection and has exhibited broad application prospects in the determination of pathogenic bacteria. In this study, the enhancement mechanisms of SERS are briefly introduced, then the characteristics and properties of liquid-phase, rigid solid-phase, and flexible solid-phase are categorized. Furthermore, a comprehensive review of the advances in label-free or label-based SERS strategies and SERS-compatible techniques for the detection of foodborne pathogens is provided, and the advantages and disadvantages of these methods are reviewed. Finally, the current challenges of SERS technology applied in practical applications are listed, and the possible development trends of SERS in the field of foodborne pathogens detection in the future are discussed.