Rapid Detection of Three Common Bacteria Based on Fluorescence Spectroscopy

High-throughput fluorescence sensing array based on tetraphenylethylene derivatives for detecting and distinguishing pathogenic microbes

Infections induced by pathogenic microorganisms will bring negative effects such as diseases that damage health and result in heavy economic burden. Therefore, it is very important to detect and identify the pathogens in time. Moreover, traditional clinical diagnosis or food testing often faces the problem of dealing with a large number of samples. Here, we designed a high-throughput fluorescent sensor array based on the different binding ability of five tetraphenylethylene derivatives (TPEs) with various side chains to different kinds of pathogenic microbes, which is used to detect and distinguish various species, so as to realize rapid mass diagnosis, and hopefully provide guidance for further determination of microbial infections and clinical treatment.

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.

Characterization and classification of pathogenic bacteria using native fluorescence and spectral deconvolution

Identification and classification of pathogenic bacterial strains is of current interest for the early treatment of diseases. In this work, protein fluorescence from eight different pathogenic bacterial strains were characterized using steady state and time resolved fluorescence spectroscopy. The spectral deconvolution method was also employed to decompose the emission contribution from different intrinsic fluorophores and extracted various key parameters, such as intensity, emission maxima, emission line width of the fluorophores, and optical redox ratio. The change in average lifetime values across different bacterial strains exhibits good statistical significance (p ≤ 0.01). The variations in the photophysical characteristics of bacterial strains are due to the different conformational states of the proteins. The stepwise multiple linear discriminate analysis of fluorescence emission spectra at 280 nm excitation across eight different bacterial strains classifies the original groups and cross validated group with 100% and 99.5% accuracy, respectively.

Primer Exchange Reaction (PER)-Based Construction of Scaffold for Low-Speed Centrifugation-Based Isolation and Quantitative Analysis of P. aeruginosa and its application in analyzing uterine secretions with intrauterine adhesion

Efficient isolation and sensitive quantification of Pseudomonas aeruginosa (P. aeruginosa) are crucial for identifying intrauterine infections and preventing the occurrence of intrauterine adhesion (IUA). However, traditional approaches, such as culture-based approach, are time-consuming. Herein, we constructed a detection scaffold by using primer exchange reaction (PER) that integrated the low-speed centrifugation-based isolation and sensitive quantification of target pathogenic bacteria. The established approach possesses several advantages, including (i) the approach is capable of simultaneous isolation and sensitive quantification of target bacteria; (ii) low-speed centrifugation or even manual equipment could be used to isolate target bacteria; and (iii) a low limit of detection was obtained as 54 cfu/mL. Based on this, the approach is a promising approach in analyzing P. aeruginosa from uterine secretions with IUA.

Fluorescence Spectroscopy Based Identification of Pseudomonas Aeruginosa and Escherichia Coli Suspensions

In this article, Fluorescence spectroscopy has been employed for the identification of Pseudomonas aeruginosa (PA) and Escherichia coli (E. coli) in water suspension. Emission spectra of PA and E. coli suspensions have been acquired by using excitation wavelengths from 270 to 420 nm with steps of 10 nm to explore their spectral features. It has been found that the emission spectra of tryptophan, tyrosine, NADH and FAD, being the intracellular biomolecules present in both bacteria, can be used as fingerprints for their identification, differentiation and quantification. Both bacterial strains can clearly be differentiated from water and from each other by using λex 270-290 nm through spectral analysis and from λex: 300-500 nm by applying statistical analysis. Furthermore, calibration curves for different bacterial loads of PA and E. coli suspensions have been produced between colonies forming units per ml (CFUs/ml) the integrated intensities of their emission spectra. CFUs/ml of both bacterial suspensions have been determined through plate count method which was used as cross-reference for the analysis of emission spectra of both bacterial suspensions. These curves may be used to estimate CFU/ml of both PA and E. coli in unknown water suspensions by determining the integrating intensity of their emission spectra.

Femtosecond laser-induced fluorescence for rapid monitoring of cardiac troponin 1 as a cardiovascular disease biomarker

Medical diagnosis usually requires blood analysis of various biomarkers which are essential for disease detection and health status monitoring. Cardiac troponin 1 (cTn1) is a protein member of the cardiac troponin complex used for the diagnosis of several pathologies associated with cardiomyocyte necrosis. Laser-induced fluorescence (LIF) is a technique with high sensitivity and specificity, and it is one of the most significant developments used as an analytical tool for qualitative and quantitative analysis. The current study investigated the potential application of femtosecond LIF as a novel detection technique for rapid monitoring of cTn1 in clinical analysis. In the present study, the cTn1 (8 ng/ml) was excited over wavelengths ranging from 350 to 400 nm, and the LIF spectra were recorded. The results demonstrated that the maximum fluorescence intensity was observed at an excitation wavelength of 350 nm, with an emitted fluorescence peak centeredat 494 nm. At an excitation wavelength of 350 nm, different concentrations of cTn1 have been investigated and LIF spectra were obtained. The results revealed that the fluorescence peak intensity is concentration-dependent and increases linearly with increasing cTn1 concentration. These findings show that femtosecond LIF presents a unique, highly selective, precise, and direct approach to monitoring cTn1.

Optical Sensors for Bacterial Detection

Analytical devices for bacterial detection are an integral part of modern laboratory medicine, as they permit the early diagnosis of diseases and their timely treatment. Therefore, special attention is directed to the development of and improvements in monitoring and diagnostic methods, including biosensor-based ones. A promising direction in the development of bacterial detection methods is optical sensor systems based on colorimetric and fluorescence techniques, the surface plasmon resonance, and the measurement of orientational effects. This review shows the detecting capabilities of these systems and the promise of electro-optical analysis for bacterial detection. It also discusses the advantages and disadvantages of optical sensor systems and the prospects for their further improvement.

Fluorescence Spectroscopy for the Assessment of Microbial Load in UVC Treated Water

In this article, Fluorescence spectroscopy has been employed for the assessment of microbial load and it has been compared with the gold standard colony forming unit (CFU) and optical density (OD) methods. In order to develop a correlation between three characterization techniques, water samples of different microbial loads have been prepared by UVC disinfection method through an indigenously developed NUVWater sterilizer, which operates in close cycle flow configuration. A UV dose of 58.9 mJ/cm2 has been determined for 99.99% disinfection for a flow rate of 0.8 l/min. The water samples were excited at 270 nm which results in the tryptophan like fluorescence at 360 nm that decreases gradually with increase of UVC dose, indicating the bacterial degradation and it has been confirmed by OD and CFU methods. In addition, it has been proved that a close cycle water flow around UV lamp is imperative so that an appropriate dose must be delivered to microorganisms for an efficient disinfection. It has been found that due to the sensitive nature of Fluorescence spectroscopy, it yields immediate results, whereas, for CFU and OD methods, water samples needs to be inoculated for 24 h. Fluorescence spectroscopy, therefore, provide a fast, online, reliable and sensitive method for the monitoring of pathogenic quantification in drinking water.

Fluorescence Spectroscopy Based Characterization of Pseudomonas Aeruginosa Suspension

In this article, optical characterization of Pseudomonas aeruginosa (PA) suspension has been performed by using Fluorescence spectroscopy. Optical density (OD) and plate count methods have been employed as a reference for the analysis of emission spectra of Pseudomonas aeruginosa in water suspension. Emission spectra of PA suspension has been acquired by using excitation wavelengths from 270 to 420 nm with step of 10 nm to explore its spectral behavior. It has been found that emission spectra of tryptophan, tyrosine, NADH and FAD, the intracellular biomolecules of bacteria, can be used as finger prints for the detection of Pseudomonas aeruginosa. Furthermore, the effect of water matrix on the spectral emission of Pseudomonas aeruginosa has been investigated that might be one of the limitation of Fluorescence spectroscopy for complex water matrices. Moreover, a calibration curve has been produced between ODs600 of Pseudomonas aeruginosa suspensions of different bacterial load and integrated intensities of the emission spectra of same samples. These ODs600 and integrating intensities have been further vetted through plate count method by determining their corresponding colony forming units per ml (CFU/ml). This calibration curve may be used to determine CFU/ml of Pseudomonas aeruginosa in water sample by determining integrating intensity of its emission spectrum.

Validation of conventional and synchronous fluorescence emission of potable water

Water from filter plants and bottled water is generally safe to drink but regular quality monitoring of these facilities requires development of quick analytical technique to ensure public safety and health. This study presented the variation of two components in spectra of conventional fluorescence spectroscopy (CFS) and four components in synchronous fluorescence spectroscopy (SFS) to assess the quality of 25 water samples from different sources. Poor quality water either due to organic or inorganic contaminants presented high intensity fluorescence emission in the blue green region and low intensity water Raman peak unlike an intense water Raman peak originated from pure water when excited at 365 nm. Emission intensity in the blue green region and water Raman peak can be used as a marker for quick screening of water quality. Although few discrepancies were observed in CF spectra of samples with intense Raman peak but were found to be positive for bacterial contamination, thus questioning the sensitivity of CFS that needs to be addressed. Whereas, SFS presented highly selective and detailed picture of water contaminants emitting aromatic amino acid, fulvic and humic like fluorescence. It is suggested that the specificity of CFS can be enhanced by coupling it with SFS or use of multiple excitation wavelengths to target different fluorophores for water quality analysis.

Transformer fault diagnosis research based on LIF technology and IAO optimization of LightGBM

Transformer fault diagnosis is a necessary operation to ensure the stable operation of a power system. In view of the problems of the low diagnostic rate and long time needed in traditional methods, such as the dissolved gas in oil method, a laser-induced fluorescence (LIF) spectral technology is proposed in this paper, which incorporated an improved aquila optimizer (IAO) and light gradient boosting machine (LightGBM), to predict the types of transformer faults. The original AO was improved using the Nelder Mead (NM) simple search method and opposition-based learning (OBL) mechanism, which could improve the parameter optimization ability of the model. Normal oil, thermal fault oil, local moisture oil, and electrical fault oil were selected as experimental samples. First, the spectral images of the four oil samples were obtained by LIF technology, and the fluorescence spectral curves obtained were preprocessed by multivariate scattering correction (MSC) and normalization (normalize), while kernel-based principle component analysis (KPCA) was used for dimensional reduction. The dimensionality-reduced data were then imported into the LightGBM model for training, and the IAO algorithm was used to optimize the parameters of the LightGBM. Finally, the experiment showed that the LIF technology demonstrated good recognition of the fault types for transformer fault diagnosis; the data purity after MSC preprocessing was higher than that of other processing methods; the prediction effect of the LightGBM model was superior to other prediction models; the LightGBM model optimized by IAO had better convergence, parameter optimization ability, and prediction accuracy than the LightGBM model optimized by the original AO and particle swarm optimization (PSO). Among the models, the MSC-IAO-LightGBM model had the best effect on fault prediction, with the mean square error (MSE) reaching 9.0643 × 10-7, mean absolute error (MAE) reaching 8.7439 × 10-4, and goodness of fit (R2) approaching 1. It can be implemented as a new diagnostic method in transformer fault detection, which is of great significance to ensure the stable and safe operation of power systems.

Advancements in Monitoring Water Quality Based on Various Sensing Methods: A Systematic Review

Nowadays, water pollution has become a global issue affecting most countries in the world. Water quality should be monitored to alert authorities on water pollution, so that action can be taken quickly. The objective of the review is to study various conventional and modern methods of monitoring water quality to identify the strengths and weaknesses of the methods. The methods include the Internet of Things (IoT), virtual sensing, cyber-physical system (CPS), and optical techniques. In this review, water quality monitoring systems and process control in several countries, such as New Zealand, China, Serbia, Bangladesh, Malaysia, and India, are discussed. Conventional and modern methods are compared in terms of parameters, complexity, and reliability. Recent methods of water quality monitoring techniques are also reviewed to study any loopholes in modern methods. We found that CPS is suitable for monitoring water quality due to a good combination of physical and computational algorithms. Its embedded sensors, processors, and actuators can be designed to detect and interact with environments. We believe that conventional methods are costly and complex, whereas modern methods are also expensive but simpler with real-time detection. Traditional approaches are more time-consuming and expensive due to the high maintenance of laboratory facilities, involve chemical materials, and are inefficient for on-site monitoring applications. Apart from that, previous monitoring methods have issues in achieving a reliable measurement of water quality parameters in real time. There are still limitations in instruments for detecting pollutants and producing valuable information on water quality. Thus, the review is important in order to compare previous methods and to improve current water quality assessments in terms of reliability and cost-effectiveness.