Raman spectroscopy-compatible inactivation method for pathogenic endospores

Combined Mutual Learning Net for Raman Spectral Microbial Strain Identification

Infectious diseases pose a significant threat to global health, yet traditional microbiological identification methods suffer from drawbacks, such as high costs and long processing times. Raman spectroscopy, a label-free and noninvasive technique, provides rich chemical information and has tremendous potential in fast microbial diagnoses. Here, we propose a novel Combined Mutual Learning Net that precisely identifies microbial subspecies. It demonstrated an average identification accuracy of 87.96% in an open-access data set with thirty microbial strains, representing a 5.76% improvement. 50% of the microbial subspecies accuracies were elevated by 1% to 46%, especially for E. coli 2 improved from 31% to 77%. Furthermore, it achieved a remarkable subspecies accuracy of 92.4% in the custom-built fiber-optical tweezers Raman spectroscopy system, which collects Raman spectra at a single-cell level. This advancement demonstrates the effectiveness of this method in microbial subspecies identification, offering a promising solution for microbiology diagnosis.

Illuminating the Tiny World: A Navigation Guide for Proper Raman Studies on Microorganisms

Raman spectroscopy is an emerging method for the identification of bacteria. Nevertheless, a lot of different parameters need to be considered to establish a reliable database capable of identifying real-world samples such as medical or environmental probes. In this review, the establishment of such reliable databases with the proper design in microbiological Raman studies is demonstrated, shining a light into all the parts that require attention. Aspects such as the strain selection, sample preparation and isolation requirements, the phenotypic influence, measurement strategies, as well as the statistical approaches for discrimination of bacteria, are presented. Furthermore, the influence of these aspects on spectra quality, result accuracy, and read-out are discussed. The aim of this review is to serve as a guide for the design of microbiological Raman studies that can support the establishment of this method in different fields.

Combining AI Tools with Non-Destructive Technologies for Crop-Based Food Safety: A Comprehensive Review

On a global scale, food safety and security aspects entail consideration throughout the farm-to-fork continuum, considering food's supply chain. Generally, the agrifood system is a multiplex network of interconnected features and processes, with a hard predictive rate, where maintaining the food's safety is an indispensable element and is part of the Sustainable Development Goals (SDGs). It has led the scientific community to develop advanced applied analytical methods, such as machine learning (ML) and deep learning (DL) techniques applied for assessing foodborne diseases. The main objective of this paper is to contribute to the development of the consensus version of ongoing research about the application of Artificial Intelligence (AI) tools in the domain of food-crop safety from an analytical point of view. Writing a comprehensive review for a more specific topic can also be challenging, especially when searching within the literature. To our knowledge, this review is the first to address this issue. This work consisted of conducting a unique and exhaustive study of the literature, using our TriScope Keywords-based Synthesis methodology. All available literature related to our topic was investigated according to our criteria of inclusion and exclusion. The final count of data papers was subject to deep reading and analysis to extract the necessary information to answer our research questions. Although many studies have been conducted, limited attention has been paid to outlining the applications of AI tools combined with analytical strategies for crop-based food safety specifically.

Comparison of the efficacy of physical and chemical strategies for the inactivation of biofilm cells of foodborne pathogens

Biofilm formation is a strategy in which microorganisms generate a matrix of extracellular polymeric substances to increase survival under harsh conditions. The efficacy of sanitization processes is lowered when biofilms form, in particular on industrial devices. While various traditional and emerging technologies have been explored for the eradication of biofilms, cell resistance under a range of environmental conditions renders evaluation of the efficacy of control challenging. This review aimed to: (1) classify biofilm control measures into chemical, physical, and combination methods, (2) discuss mechanisms underlying inactivation by each method, and (3) summarize the reduction of biofilm cells after each treatment. The review is expected to be useful for future experimental studies and help to guide the establishment of biofilm control strategies in the food industry.

Physico-chemical characterization of single bacteria and spores using optical tweezers

Spore-forming pathogenic bacteria are adapted for adhering to surfaces, and their endospores can tolerate strong chemicals making decontamination difficult. Understanding the physico-chemical properties of bacteria and spores is therefore essential in developing antiadhesive surfaces and disinfection techniques. However, measuring physico-chemical properties in bulk does not show the heterogeneity between cells. Characterizing bacteria on a single-cell level can thereby provide mechanistic clues usually hidden in bulk measurements. This paper shows how optical tweezers can be applied to characterize single bacteria and spores, and how physico-chemical properties related to adhesion, fluid dynamics, biochemistry, and metabolic activity can be assessed.

Hypervirulent R20291 Clostridioides difficile spores show disinfection resilience to sodium hypochlorite despite structural changes

BACKGROUND

Clostridioides difficile is a spore forming bacterial species and the major causative agent of nosocomial gastrointestinal infections. C. difficile spores are highly resilient to disinfection methods and to prevent infection, common cleaning protocols use sodium hypochlorite solutions to decontaminate hospital surfaces and equipment. However, there is a balance between minimising the use of harmful chemicals to the environment and patients as well as the need to eliminate spores, which can have varying resistance properties between strains. In this work, we employ TEM imaging and Raman spectroscopy to analyse changes in spore physiology in response to sodium hypochlorite. We characterize different C. difficile clinical isolates and assess the chemical's impact on spores' biochemical composition. Changes in the biochemical composition can, in turn, change spores' vibrational spectroscopic fingerprints, which can impact the possibility of detecting spores in a hospital using Raman based methods.

RESULTS

We found that the isolates show significantly different susceptibility to hypochlorite, with the R20291 strain, in particular, showing less than 1 log reduction in viability for a 0.5% hypochlorite treatment, far below typically reported values for C. difficile. While TEM and Raman spectra analysis of hypochlorite-treated spores revealed that some hypochlorite-exposed spores remained intact and not distinguishable from controls, most spores showed structural changes. These changes were prominent in B. thuringiensis spores than C. difficile spores.

CONCLUSION

This study highlights the ability of certain C. difficile spores to survive practical disinfection exposure and the related changes in spore Raman spectra that can be seen after exposure. These findings are important to consider when designing practical disinfection protocols and vibrational-based detection methods to avoid a false-positive response when screening decontaminated areas.

Mode of Action of Disinfection Chemicals on the Bacterial Spore Structure and Their Raman Spectra

Contamination of toxic spore-forming bacteria is problematic since spores can survive a plethora of disinfection chemicals and it is hard to rapidly detect if the disinfection chemical has inactivated the spores. Thus, robust decontamination strategies and reliable detection methods to identify dead from viable spores are critical. In this work, we investigate the chemical changes of Bacillus thuringiensis spores treated with sporicidal agents such as chlorine dioxide, peracetic acid, and sodium hypochlorite using laser tweezers Raman spectroscopy. We also image treated spores using SEM and TEM to verify if we can correlate structural changes in the spores with changes to their Raman spectra. We found that over 30 min, chlorine dioxide did not change the Raman spectrum or the spore structure, peracetic acid showed a time-dependent decrease in the characteristic DNA/DPA peaks and ∼20% of the spores were degraded and collapsed, and spores treated with sodium hypochlorite showed an abrupt drop in DNA and DPA peaks within 20 min and some structural damage to the exosporium. Structural changes appeared in spores after 10 min, compared to the inactivation time of the spores, which is less than a minute. We conclude that vibrational spectroscopy provides powerful means to detect changes in spores but it might be problematic to identify if spores are live or dead after a decontamination procedure.

Rapid detection of bacterial infection and viability assessment with high specificity and sensitivity using Raman microspectroscopy

Infectious diseases caused by bacteria still pose major diagnostic challenges in spite of the availability of various molecular approaches. Irrespective of the type of infection, rapid identification of the causative pathogen with a high degree of sensitivity and specificity is essential for initiating appropriate treatment. While existing methods like PCR possess high sensitivity, they are incapable of identifying the viability status of the pathogen and those which can, like culturing, are inherently slow. To overcome these limitations, we developed a diagnostic platform based on Raman microspectroscopy, capable of detecting biochemical signatures from a single bacterium for identification as well as viability assessment. The study also establishes a decontamination protocol for handling live pathogenic bacteria which does not affect identification and viability testing, showing applicability in the analysis of sputum samples containing pathogenic mycobacterial strains. The minimal sample processing along with multivariate analysis of spectroscopic signatures provides an interface for automatic classification, allowing the prediction of unknown samples by mapping signatures onto available datasets. Also, the novelty of the current work is the demonstration of simultaneous identification and viability assessment at a single bacterial level for pathogenic bacteria. Graphical abstract.

A Machine Learning-Based Raman Spectroscopic Assay for the Identification of Burkholderia mallei and Related Species

Burkholderia (B.) mallei, the causative agent of glanders, and B. pseudomallei, the causative agent of melioidosis in humans and animals, are genetically closely related. The high infectious potential of both organisms, their serological cross-reactivity, and similar clinical symptoms in human and animals make the differentiation from each other and other Burkholderia species challenging. The increased resistance against many antibiotics implies the need for fast and robust identification methods. The use of Raman microspectroscopy in microbial diagnostic has the potential for rapid and reliable identification. Single bacterial cells are directly probed and a broad range of phenotypic information is recorded, which is subsequently analyzed by machine learning methods. Burkholderia were handled under biosafety level 1 (BSL 1) conditions after heat inactivation. The clusters of the spectral phenotypes and the diagnostic relevance of the Burkholderia spp. were considered for an advanced hierarchical machine learning approach. The strain panel for training involved 12 B. mallei, 13 B. pseudomallei and 11 other Burkholderia spp. type strains. The combination of top- and sub-level classifier identified the mallei-complex with high sensitivities (>95%). The reliable identification of unknown B. mallei and B. pseudomallei strains highlighted the robustness of the machine learning-based Raman spectroscopic assay.

Raman spectroscopy reveals distinct differences between two closely related bacterial strains, Mycobacterium indicus pranii and Mycobacterium intracellulare

A common technique used to differentiate bacterial species and to determine evolutionary relationships is sequencing their 16S ribosomal RNA genes. However, this method fails when organisms exhibit high similarity in these sequences. Two such strains that have identical 16S rRNA sequences are Mycobacterium indicus pranii (MIP) and Mycobacterium intracellulare. MIP is of significance as it is used as an adjuvant for protection against tuberculosis and leprosy; in addition, it shows potent anti-cancer activity. On the other hand, M. intracellulare is an opportunistic pathogen and causes severe respiratory infections in AIDS patients. It is important to differentiate these two bacterial species as they co-exist in immuno-compromised individuals. To unambiguously distinguish these two closely related bacterial strains, we employed Raman and resonance Raman spectroscopy in conjunction with multivariate statistical tools. Phenotypic profiling for these bacterial species was performed in a kinetic manner. Differences were observed in the mycolic acid profile and carotenoid pigments to show that MIP is biochemically distinct from M. intracellulare. Resonance Raman studies confirmed that carotenoids were produced by both MIP as well as M. intracellulare, though the latter produced higher amounts. Overall, this study demonstrates the potential of Raman spectroscopy in differentiating two closely related mycobacterial strains. Graphical abstract.

Effect of Chlorine and Temperature on Larvicidal Activity of Cuban Bacillus thuringiensis Isolates

BACKGROUND

The efficacy of biolarvicides may be influenced by species of mosquito, larval age and density, temperature, water quality, bacterial formulation, and others. The aim of this study was to evaluate the influence of temperature and chlorine on larvicidal activity of Bacillus thuringiensis Cuban isolates against Aedes aegypti.

METHODS

The influence of temperature (25, 30, 35 °C) and chlorine (2.25mg/L) on the larvicidal activity of eleven B. thuringiensis Cuban isolates (collected between 2007 and 2009) were tested under laboratory conditions following WHO protocols. Bioassay data were analyzed by Probit program. The effect of chlorine and temperature (25, 30, 35 and 40 °C) on the Cry and Cyt proteins of these isolates was determined by SDS-PAGE polyacrylamide gel electrophoresis.

RESULTS

The pathogenicity of the isolates U81, X48 was affected at 35 °C. However, A21, A51, L910, and R89 isolates increase their entomopathogen activity at 35 °C. No differences were observed in toxicity of M29, R84, R85 and R87 isolates at different temperatures. The Cry 4, Cry 10 and Cry 11 proteins were reduced in A21, X48, R85 isolates at 35 and 40 °C. The Cyt proteins were reduced at 35 and 40 °C in A21, X48, R85, and A51 isolates. In L910 and R84 isolates, the Cyt toxin was degraded only at 40 °C. In chlorinated water, the lethal concentrations 50 and 90 in A21, A51, M29, R84, U81, and X48 isolates were increase.

CONCLUSION

A21, A51, L910, R85, and X48 isolates have a strong larvicidal activity for the treatment of Ae. aegypti breeding's sites exposed to high temperature and chlorine.

Resistance and Raman spectroscopy analysis of Parageobacillus thermantarcticus spores after γ-ray exposure

Spores of the genus Bacillus are able to resist ionizing radiations and therefore they are a suitable biological model for studies in Astrobiology, i.e. the multidisciplinary approach to the study of the origin and evolution of life on Earth and in the universe. The resistance to γ-radiation is an important issue in Astrobiology in relation to the search for bacterial species that could adapt to life in space. This study investigates the resistance of spores of the thermophilic bacteria Parageobacillus thermantarcticus to γ-rays. The analysis of spores' response to irradiation at a molecular level is performed by means of Raman spectroscopy that allows to get insights in the sequence of events taking place during inactivation. The role of the γ-rays' dose in the inactivation of spores is also investigated, allowing to highlight the mechanism(s) of inactivation including DNA damage, protein denaturation and calcium dipicolinate levels.

Single-cell level methods for studying the effect of antibiotics on bacteria during infection

Considerable evidence about phenotypic heterogeneity among bacteria during infection has accumulated during recent years. This heterogeneity has to be considered if the mechanisms of infection and antibiotic action are to be understood, so we need to implement existing and find novel methods to monitor the effects of antibiotics on bacteria at the single-cell level. This review provides an overview of methods by which this aim can be achieved. Fluorescence label-based methods and Raman scattering as a label-free approach are discussed in particular detail. Other label-free methods that can provide single-cell level information, such as impedance spectroscopy and surface plasmon resonance, are briefly summarized. The advantages and disadvantages of these different methods are discussed in light of a challenging in vivo environment.

Isolation and identification of bacteria by means of Raman spectroscopy

Bacterial detection is a highly topical research area, because various fields of application will benefit from the progress being made. Consequently, new and innovative strategies which enable the investigation of complex samples, like body fluids or food stuff, and improvements regarding the limit of detection are of general interest. Within this review the prospects of Raman spectroscopy as a reliable tool for identifying bacteria in complex samples are discussed. The main emphasis of this work is on important aspects of applying Raman spectroscopy for the detection of bacteria like sample preparation and the identification process. Several approaches for a Raman compatible isolation of bacterial cells have been developed and applied to different matrices. Here, an overview of the limitations and possibilities of these methods is provided. Furthermore, the utilization of Raman spectroscopy for diagnostic purposes, food safety and environmental issues is discussed under a critical view.

Chemical fixation methods for Raman spectroscopy-based analysis of bacteria

Preservation of biological samples for downstream analysis is important for analytical methods that measure the biochemical composition of a sample. One such method, Raman microspectroscopy, is commonly used as a rapid phenotypic technique to measure biomolecular composition for the purposes of identification and discrimination of species and strains of bacteria, as well as investigating physiological responses to external stressors and the uptake of stable isotope-labelled substrates in single cells. This study examines the influence of a number of common chemical fixation and inactivation methods on the Raman spectrum of six species of bacteria. Modifications to the Raman-phenotype caused by fixation were compared to unfixed control samples using difference spectra and Principal Components Analysis (PCA). Additionally, the effect of fixation on the ability to accurately classify bacterial species using their Raman phenotype was determined. The results showed that common fixatives such as glutaraldehyde and ethanol cause significant changes to the Raman spectra of bacteria, whereas formaldehyde and sodium azide were better at preserving spectral features.

Antimicrobial properties of CuO nanorods and multi-armed nanoparticles against B. anthracis vegetative cells and endospores

Two different kinds of CuO nanoparticles (NPs) namely CuO nanorods (PS2) and multi-armed nanoparticles (P5) were synthesized by wet and electrochemical routes, respectively. Their structure, morphology, size and compositions were characterized by SEM, EDX and XRD. The NPs demonstrated strong bactericidal potential against Bacillus anthracis cells and endospores. PS2 killed 92.17% of 4.5 × 10(4) CFU/mL B. anthracis cells within 1 h at a dose of 1 mg/mL. Whereas P5 showed a higher efficacy by killing 99.92% of 7 × 10(5) CFU/mL B. anthracis cells within 30 min at a dose of 0.5 mg/mL and 99.6% of 1.25 × 10(4) CFU/mL B. anthracis cells within 5 min at a dose of 2 mg/mL. More than 99% of spores were killed within 8 h with 2 mg/mL PS2 in LB media.

Isolation and enrichment of pathogens with a surface-modified aluminium chip for Raman spectroscopic applications

We developed a Raman-compatible chip for isolating microorganisms from complex media. The isolation of bacteria is achieved by using antibodies as capture molecules. Due to the very specific interaction with the targets, this approach is promising for isolation of bacteria even from complex matrices such as body fluids. Our choice of capture molecules also enabled the investigation of samples containing yet unidentified bacteria, as the antibodies can capture a large variety of bacteria based on their analogue cell wall surface structures. The capability of our system is demonstrated for a broad range of different Gram-positive and Gram-negative germs. Subsequent identification is done by recording Raman spectra of the bacteria. Further, it is shown that classification with chemometric methods is possible.

Comprehensive detection and discrimination of Campylobacter species by use of confocal micro-Raman spectroscopy and multilocus sequence typing

A novel strategy for the rapid detection and identification of traditional and emerging Campylobacter strains based upon Raman spectroscopy (532 nm) is presented here. A total of 200 reference strains and clinical isolates of 11 different Campylobacter species recovered from infected animals and humans from China and North America were used to establish a global Raman spectroscopy-based dendrogram model for Campylobacter identification to the species level and cross validated for its feasibility to predict Campylobacter-associated food-borne outbreaks. Bayesian probability coupled with Monte Carlo estimation was employed to validate the established Raman classification model on the basis of the selected principal components, mainly protein secondary structures, on the Campylobacter cell membrane. This Raman spectroscopy-based typing technique correlates well with multilocus sequence typing and has an average recognition rate of 97.21%. Discriminatory power for the Raman classification model had a Simpson index of diversity of 0.968. Intra- and interlaboratory reproducibility with different instrumentation yielded differentiation index values of 4.79 to 6.03 for wave numbers between 1,800 and 650 cm(-1) and demonstrated the feasibility of using this spectroscopic method at different laboratories. Our Raman spectroscopy-based partial least-squares regression model could precisely discriminate and quantify the actual concentration of a specific Campylobacter strain in a bacterial mixture (regression coefficient, >0.98; residual prediction deviation, >7.88). A standard protocol for sample preparation, spectral collection, model validation, and data analyses was established for the Raman spectroscopic technique. Raman spectroscopy may have advantages over traditional genotyping methods for bacterial epidemiology, such as detection speed and accuracy of identification to the species level.

Raman spectroscopy as a potential tool for detection of Brucella spp. in milk

Detection of Brucella, causing brucellosis, is very challenging, since the applied techniques are mostly time-demanding and not standardized. While the common detection system relies on the cultivation of the bacteria, further classical typing up to the biotype level is mostly based on phenotypic or genotypic characteristics. The results of genotyping do not always fit the existing taxonomy, and misidentifications between genetically closely related genera cannot be avoided. This situation gets even worse, when detection from complex matrices, such as milk, is necessary. For these reasons, the availability of a method that allows early and reliable identification of possible Brucella isolates for both clinical and epidemiological reasons would be extremely useful. We evaluated micro-Raman spectroscopy in combination with chemometric analysis to identify Brucella from agar plates and directly from milk: prior to these studies, the samples were inactivated via formaldehyde treatment to ensure a higher working safety. The single-cell Raman spectra of different Brucella, Escherichia, Ochrobactrum, Pseudomonas, and Yersinia spp. were measured to create two independent databases for detection in media and milk. Identification accuracies of 92% for Brucella from medium and 94% for Brucella from milk were obtained while analyzing the single-cell Raman spectra via support vector machine. Even the identification of the other genera yielded sufficient results, with accuracies of >90%. In summary, micro-Raman spectroscopy is a promising alternative for detecting Brucella. The measurements we performed at the single-cell level thus allow fast identification within a few hours without a demanding process for sample preparation.

Online-calibration for reliable and robust lab-on-a-chip surface enhanced Raman spectroscopy measurement in a liquid/liquid segmented flow

Concerning the usability of lab-on-a-chip surface enhanced Raman spectroscopy (LOC-SERS) for analytical tasks applying chemometric data evalutation, a secure, reproducible, and stable data output independent of inconsistent ambient conditions has to be accomplished. In this contribution, we present a new approach to achieve reliable and robust measurements based on segmented flow LOC-SERS via online-wavenumber calibration.

Investigating antibacterial effects of garlic (Allium sativum) concentrate and garlic-derived organosulfur compounds on Campylobacter jejuni by using Fourier transform infrared spectroscopy, Raman spectroscopy, and electron microscopy

Fourier transform infrared (FT-IR) spectroscopy and Raman spectroscopy were used to study the cell injury and inactivation of Campylobacter jejuni from exposure to antioxidants from garlic. C. jejuni was treated with various concentrations of garlic concentrate and garlic-derived organosulfur compounds in growth media and saline at 4, 22, and 35°C. The antimicrobial activities of the diallyl sulfides increased with the number of sulfur atoms (diallyl sulfide < diallyl disulfide < diallyl trisulfide). FT-IR spectroscopy confirmed that organosulfur compounds are responsible for the substantial antimicrobial activity of garlic, much greater than those of garlic phenolic compounds, as indicated by changes in the spectral features of proteins, lipids, and polysaccharides in the bacterial cell membranes. Confocal Raman microscopy (532-nm-gold-particle substrate) and Raman mapping of a single bacterium confirmed the intracellular uptake of sulfur and phenolic components. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were employed to verify cell damage. Principal-component analysis (PCA), discriminant function analysis (DFA), and soft independent modeling of class analogs (SIMCA) were performed, and results were cross validated to differentiate bacteria based upon the degree of cell injury. Partial least-squares regression (PLSR) was employed to quantify and predict actual numbers of healthy and injured bacterial cells remaining following treatment. PLSR-based loading plots were investigated to further verify the changes in the cell membrane of C. jejuni treated with organosulfur compounds. We demonstrated that bacterial injury and inactivation could be accurately investigated by complementary infrared and Raman spectroscopies using a chemical-based, "whole-organism fingerprint" with the aid of chemometrics and electron microscopy.