Label‐free surface‐enhanced Raman spectroscopy coupled with machine learning algorithms in pathogenic microbial identification: Current trends, challenges, and perspectives

Deleted Journal, Год журнала: 2024, Номер 2(3)

Опубликована: Март 5, 2024

Abstract Infectious diseases caused by microbial pathogens remain a primary contributor to global health burdens. Prompt control and effective prevention of these are critical for public medical diagnostics. Conventional detection methods suffer from high complexity, low sensitivity, poor selectivity. Therefore, developing rapid reliable pathogen has become imperative. Surface‐enhanced Raman Spectroscopy (SERS), as an innovative non‐invasive diagnostic technique, holds significant promise in pathogenic microorganism due its rapid, reliable, cost‐effective advantages. This review comprehensively outlines the fundamental theories (RS) with focus on label‐free SERS strategy, reporting latest advancements technique detecting bacteria, viruses, fungi clinical settings. Furthermore, we emphasize application machine learning algorithms spectral analysis. Finally, challenges faced probed, prospective development is discussed.

Язык: Английский

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Identification of hypermucoviscous Klebsiella pneumoniae K1, K2, K54 and K57 capsular serotypes by Raman spectroscopy

Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, Год журнала: 2024, Номер 319, С. 124533 - 124533

Опубликована: Май 27, 2024

Antimicrobial resistance poses a significant challenge in modern medicine, affecting public health. Klebsiella pneumoniae infections compound this issue due to their broad range of and the emergence multiple antibiotic mechanisms. Efficient detection its capsular serotypes is crucial for immediate patient treatment, epidemiological tracking outbreak containment. Current methods have limitations that can delay interventions increase risk morbidity mortality. Raman spectroscopy promising alternative identify hypermucoviscous K. isolates. It provides rapid situ measurements with minimal sample preparation. Moreover, combination machine learning tools demonstrates high accuracy reproducibility. This study analyzed viability combining one-dimensional convolutional neural networks (1-D CNN) classify four pneumoniae: K1, K2, K54 K57. Our approach involved identifying most relevant features classification prevent overfitting training models. Simplifying dataset essential information maintains reduces computational costs time. Capsular were classified 96% using less than 30 out 2400 contained each spectrum. To validate our methodology, we expanded include both non-mucoid isolates distinguished between them. resulted an rate 94%. The results obtained potential practical healthcare applications, especially enabling prompt prescription appropriate treatment against infections.

Язык: Английский

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Recent Advances in Bacterial Detection Using Surface-Enhanced Raman Scattering

Biosensors, Год журнала: 2024, Номер 14(8), С. 375 - 375

Опубликована: Авг. 1, 2024

Rapid identification of microorganisms with a high sensitivity and selectivity is great interest in many fields, primarily clinical diagnosis, environmental monitoring, the food industry. For over past decades, surface-enhanced Raman scattering (SERS)-based detection platform has been extensively used for bacterial detection, effort extended to clinical, environmental, samples. In contrast other approaches, such as enzyme-linked immunosorbent assays polymerase chain reaction, SERS exhibits outstanding advantages rapid being culture-free, low cost, sensitivity, lack water interference. This review aims cover development SERS-based methods an emphasis on source signal, techniques improve limit specificity, application high-throughput settings complex The challenges advancements implementation artificial intelligence (AI) are also discussed.

Язык: Английский

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Surface-Enhanced Raman Spectroscopy (SERS) for the Characterization of Biofilm Forming and Non-Biofilm Forming Klebsiella pneumoniae Strains

Analytical Letters, Год журнала: 2025, Номер unknown, С. 1 - 20

Опубликована: Янв. 3, 2025

Surface-enhanced Raman spectroscopy (SERS) is an effective technique for identifying the biochemical composition of biofilm forming bacterial strains which exhibit strong antibiotic resistance and present major challenges in healthcare settings. Klebsiella pneumoniae, opportunistic pathogen known its ability to form biofilms, responsible a variety nosocomial community-infections, highlighting critical need precise detection. In this study, nine different K. pneumoniae were selected categorized according their capacity (non-biofilm, medium biofilm, biofilm). The silver nanoparticles (Ag-NPs) based SERS approach was used analyze differences between cell mass (pellets) these strains. Principal component analysis (PCA) partial least squares discriminant applied classify differentiate spectral datasets, achieving 100% specificity 81.82% sensitivity. This enables accurate rapid identification strains, along with detailed profiling matrix.

Язык: Английский

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Study of interaction in dual-species biofilm of Candida glabrata and Klebsiella pneumoniae co-isolated from peripheral venous catheter using Raman characterization mapping and machine learning algorithms

Microbial Pathogenesis, Год журнала: 2025, Номер 199, С. 107280 - 107280

Опубликована: Янв. 5, 2025

Язык: Английский

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Carbapenem-Resistant Klebsiella pneumoniae: A comprehensive review of phenotypic and genotypic methods for detection

The Microbe, Год журнала: 2025, Номер unknown, С. 100246 - 100246

Опубликована: Янв. 1, 2025

Язык: Английский

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Harnessing advanced molecular diagnostics and bioinformatics to ascertain antimicrobial resistance in ESKAPE organisms

The Microbe, Год журнала: 2025, Номер 7, С. 100316 - 100316

Опубликована: Апрель 1, 2025

Язык: Английский

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Proteome analysis, genetic characterization, and antibiotic resistance patterns of Klebsiella pneumoniae clinical isolates

AMB Express, Год журнала: 2024, Номер 14(1)

Опубликована: Май 9, 2024

Klebsiella pneumoniae (K. pneumoniae) is a member of the ESKAPE group and responsible for severe community healthcare-associated infections. Certain species have very similar phenotypes, which presents challenge in identifying K. pneumoniae. Multidrug-resistant also serious global problem that needs to be addressed. A total 190 isolates were isolated from urine (n = 69), respiratory 52), wound 48) blood 21) samples collected various hospitals Al-Qassim, Saudi Arabia, between March 2021 October 2022. Our study aimed rapidly accurately detect using Peptide Mass Fingerprinting (PMF) technique, confirmed by real-time PCR. Additionally, screening antibiotic susceptibility resistance was conducted. The primary methods culture, Gram staining, Vitek® 2 ID Compact system. An automated MALDI Biotyper (MBT) instrument used proteome identification, subsequently SYBR green polymerase chain reaction (real-time PCR) microfluidic electrophoresis assays. AST-GN66 cards utilized evaluate antimicrobial sensitivity isolates. According our results, identified 178 out (93.68%) isolates, while PMF technique correctly detected 188 (98.95%) with score value 2.00 or higher. Principal component analysis conducted MBT Compass software classify based on their structure. Based single peak intensities generated MBT, highest values found at 3444, 5022, 5525, 6847, 7537 m/z. gene testing 90.53% detecting entrobactin, 70% 16 S rRNA, 32.63% ferric iron uptake. antibiotics as follows: 64.75% cefazolin, 62.63% trimethoprim/sulfamethoxazole, 59.45% ampicillin, 58.42% cefoxitin, 57.37% ceftriaxone, 53.68% cefepime, 52.11% ampicillin-sulbactam, 50.53% ceftazidime, ertapenem, 49.47% imipenem. results double-disk synergy test, 93 (48.95%) extended-spectrum beta-lactamase. In conclusion, powerful analytical identify clinical proteomic characteristics. shown increasing different classes, including carbapenem, poses significant threat human health these infections may become difficult treat.

Язык: Английский

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Rapid discrimination between wild and cultivated Ophiocordyceps sinensis through comparative analysis of label-free SERS technique and mass spectrometry

Current Research in Food Science, Год журнала: 2024, Номер 9, С. 100820 - 100820

Опубликована: Янв. 1, 2024

Ophiocordyceps sinensis is a genus of ascomycete fungi that has been widely used as valuable tonic or medicine. However, due to over-exploitation and the destruction natural ecosystems, shortage wild O. resources led an increase in artificially cultivated sinensis. To rapidly accurately identify molecular differences between sinensis, this study employs surface-enhanced Raman spectroscopy (SERS) combined with machine learning algorithms distinguish two categories. Specifically, we collected SERS spectra for validated metabolic profiles using Ultra-Performance Liquid Chromatography coupled Orbitrap High-Resolution Mass Spectrometry (UPLC-Orbitrap-HRMS). Subsequently, constructed classifiers mine potential information from spectral data, feature importance map determined through optimized algorithm. The results indicate representative characteristic peaks are consistent metabolites identified metabolomics analysis, confirming feasibility method. support vector (SVM) model achieved most accurate efficient capacity discriminating (accuracy = 98.95%, 5-fold cross-validation 98.38%, time 0.89s). revealed subtle compositional Taken together, these expected enable application quality control raw materials, providing foundation rapid identification their origin.

Язык: Английский

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Genetic diversity of Plasmodium vivax and Plasmodium falciparum field isolates from Honduras in the malaria elimination phase

Current Research in Parasitology and Vector-Borne Diseases, Год журнала: 2024, Номер 7, С. 100230 - 100230

Опубликована: Ноя. 21, 2024

Malaria continues to be a major threat public health in tropical regions, primarily affecting sub-Saharan Africa but also Asia, the Middle East, and Latin America. cases Honduras have seen significant decline country aims eliminate disease by 2030. This study examines genetic diversity of

Язык: Английский

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