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

Raman-Activated Cell Ejection for Validating the Reliability of the Raman Fingerprint Database of Foodborne Pathogens

Raman spectroscopy for rapid identification of foodborne pathogens based on phenotype has attracted increasing attention, and the reliability of the Raman fingerprint database through genotypic determination is crucial. In the research, the classification model of four foodborne pathogens was established based on t-distributed stochastic neighbor embedding (t-SNE) and support vector machine (SVM); the recognition accuracy was 97.04%. The target bacteria named by the model were ejected through Raman-activated cell ejection (RACE), and then single-cell genomic DNA was amplified for species analysis. The accuracy of correct matches between the predicted phenotype and the actual genotype of the target cells was at least 83.3%. Furthermore, all anticipant sequencing results brought into correspondence with the species were predicted through the model. In sum, the Raman fingerprint database based on Raman spectroscopy combined with machine learning was reliable and promising in the field of rapid detection of foodborne pathogens.

New insights into the effects of UV light on individual Nosema bombycis spores, as determined using single-cell optical approaches

Nosema bombycis (Nb) is a pathogen causing pebrine in sericulture. Ultraviolet (UV) light exposure is a common physical disinfection method, but the mechanisms underlying UV-based disinfection have only been studied at the population level. In this study, changes in and germination of UV-irradiated spores were observed using Raman tweezers and phase-contrast imaging to evaluate the effects of UV radiation on Nb spores at the single-cell level. We found that irradiation caused the complete leakage of trehalose from individual spores. We also found that more spores leaked as the UV dose increased. There was no significant loss of intracellular biomacromolecules and no marked changes in the peaks associated with protein secondary structures. Low-dose radiation promoted spore germination and high-dose radiation decreased the germination rate, while the germination time did not undergo significant alterations. These results suggest that UV radiation disrupts the permeability of the inner membrane and alters the spore wall, thereby affecting the ability of the spore to sense and respond to extracellular stimuli, which further triggers germination and reduces or stops spore germination. This study provides new insights into the molecular mechanisms underlying conventional disinfection measures on microsporidian spores.

Recent advances in microfluidic-based spectroscopic approaches for pathogen detection

Rapid identification of pathogens with higher sensitivity and specificity plays a significant role in maintaining public health, environmental monitoring, controlling food quality, and clinical diagnostics. Different methods have been widely used in food testing laboratories, quality control departments in food companies, hospitals, and clinical settings to identify pathogens. Some limitations in current pathogens detection methods are time-consuming, expensive, and laborious sample preparation, making it unsuitable for rapid detection. Microfluidics has emerged as a promising technology for biosensing applications due to its ability to precisely manipulate small volumes of fluids. Microfluidics platforms combined with spectroscopic techniques are capable of developing miniaturized devices that can detect and quantify pathogenic samples. The review focuses on the advancements in microfluidic devices integrated with spectroscopic methods for detecting bacterial microbes over the past five years. The review is based on several spectroscopic techniques, including fluorescence detection, surface-enhanced Raman scattering, and dynamic light scattering methods coupled with microfluidic platforms. The key detection principles of different approaches were discussed and summarized. Finally, the future possible directions and challenges in microfluidic-based spectroscopy for isolating and detecting pathogens using the latest innovations were also discussed.

Characterization of individual spores of two biological insecticides, Bacillus thuringiensis and Lysinibacillus sphaericus, in response to glutaraldehyde using single-cell optical approaches

Bacillus thuringiensis (Bt) and Lysinibacillus sphaericus (Ls) are the most widely used microbial insecticides. Both encounter unfavorable environmental factors and pesticides in the field. Here, the responses of Bt and Ls spores to glutaraldehyde were characterized using Raman spectroscopy and differential interference contrast imaging at the single-cell level. Bt spores were more sensitive to glutaraldehyde than Ls spores under prolonged exposure: <1.0% of Bt spores were viable after 10 min of 0.5% (v/v) glutaraldehyde treatment, compared to ~ 20% of Ls spores. The Raman spectra of glutaraldehyde-treated Bt and Ls spores were almost identical to those of untreated spores; however, the germination process of individual spores was significantly altered. The time to onset of germination, the period of rapid Ca2+-2,6-pyridinedicarboxylic acid (CaDPA) release, and the period of cortex hydrolysis of treated Bt spores were significantly longer than those of untreated spores, with dodecylamine germination being particularly affected. Similarly, the germination of treated Ls spores was significantly prolonged, although the prolongation was less than that of Bt spores. Although the interiors of Bt and Ls spores were undamaged and CaDPA did not leak, proteins and structures involved in spore germination could be severely damaged, resulting in slower and significantly prolonged germination. This study provides insights into the impact of glutaraldehyde on bacterial spores at the single cell level and the variability in spore response to glutaraldehyde across species and populations.

Terahertz spectra reconstructed using convolutional denoising autoencoder for identification of rice grains infested with Sitophilus oryzae at different growth stages

Rice grains are often infected by Sitophilus oryzae due to improper storage, resulting in quality and quantity losses. The efficacy of terahertz time-domain spectroscopy (THz-TDS) technology in detecting Sitophilus oryzae at different stages of infestation in stored rice was employed in the current research. Terahertz (THz) spectra for rice grains infested by Sitophilus oryzae at different growth stages were acquired. Then, the convolutional denoising autoencoder (CDAE) was used to reconstruct THz spectra to reduce the noise-to-signal ratio. Finally, a random forest classification (RFC) model was developed to identify the infestation levels. Results showed that the RFC model based on the reconstructed second-order derivative spectrum with an accuracy of 84.78%, a specificity of 86.75%, a sensitivity of 86.36% and an F1-score of 85.87% performed better than the original first-order derivative THz spectrum with an accuracy of 89.13%, a specificity of 91.38%, a sensitivity of 88.18% and an F1-score of 89.16%. In addition, the convolutional layers inside the CDAE were visualized using feature maps to explain the improvement in results, illustrating that the CDAE can eliminate noise in the spectral data. Overall, THz spectra reconstructed with the CDAE provided a novel method for effective THz detection of infected grains.

Regulating bacterial biofilms in food and biomedicine: unraveling mechanisms and Innovating strategies

Bacterial biofilm has brought a lot of intractable problems in food and biomedicine areas. Conventional biofilm control mainly focuses on inactivation and removal of biofilm. However, with robust construction and enhanced resistance, the established biofilm is extremely difficult to eradicate. According to the mechanism of biofilm development, biofilm formation can be modulated by intervening in the key factors and regulatory systems. Therefore, regulation of biofilm formation has been proposed as an alternative way for effective biofilm control. This review aims to provide insights into the regulation of biofilm formation in food and biomedicine. The underlying mechanisms for early-stage biofilm establishment are summarized based on the key factors and correlated regulatory networks. Recent developments and applications of novel regulatory strategies such as anti/pro-biofilm agents, nanomaterials, functionalized surface materials and physical strategies are also discussed. The current review indicates that these innovative methods have contributed to effective biofilm control in a smart, safe and eco-friendly way. However, standard methodology for regulating biofilm formation in practical use is still missing. As biofilm formation in real-world systems could be far more complicated, further studies and interdisciplinary collaboration are still needed for simulation and experiments in the industry and other open systems.

Bifidobacterium species viability in dairy-based probiotic foods: challenges and innovative approaches for accurate viability determination and monitoring of probiotic functionality

Bifidobacterium species are essential members of a healthy human gut microbiota. Their presence in the gut is associated with numerous health outcomes such as protection against gastrointestinal tract infections, inflammation, and metabolic diseases. Regular intake of Bifidobacterium in foods is a sustainable way of maintaining the health benefits associated with its use as a probiotic. Owing to their global acceptance, fermented dairy products (particularly yogurt) are considered the ideal probiotic carrier foods. As envisioned in the definition of probiotics as "live organisms," the therapeutic functionalities of Bifidobacterium spp. depend on maintaining their viability in the foods up to the point of consumption. However, sustaining Bifidobacterium spp. viability during the manufacture and shelf-life of fermented dairy products remains challenging. Hence, this paper discusses the significance of viability as a prerequisite for Bifidobacterium spp. probiotic functionality. The paper focuses on the stress factors that influence Bifidobacterium spp. viability during the manufacture and shelf life of yogurt as an archetypical fermented dairy product that is widely accepted as a delivery vehicle for probiotics. It further expounds the Bifidobacterium spp. physiological and genetic stress response mechanisms as well as the methods for viability retention in yogurt, such as microencapsulation, use of oxygen scavenging lactic acid bacterial strains, and stress-protective agents. The report also explores the topic of viability determination as a critical factor in probiotic quality assurance, wherein, the limitations of culture-based enumeration methods, the challenges of species and strain resolution in the presence of lactic acid bacterial starter and probiotic species are discussed. Finally, new developments and potential applications of next-generation viability determination methods such as flow cytometry, propidium monoazide-quantitative polymerase chain reaction (PMA-qPCR), next-generation sequencing, and single-cell Raman spectroscopy (SCRS) methods are examined.

A durian-shaped multilayer core-shell SERS substrate for flow magnetic detection of pesticide residues on foods

A new type of durian-shaped Fe3O4@Au@Ag@Au (DFAAA) multilayer core-shell composite was prepared as an efficient surface-enhanced Raman scattering (SERS) substrate. The optimization process and SERS enhancement mechanism of the substrate were further explained with finite-difference time-domain simulation. The dense and uniform spiny array on the DFAAA surface had abundant "hot spots", greatly improving sensitivity, uniformity and reproducibility, with a Raman enhancement factor of 3.01 × 107 and storage-life of 30 d. A "flow magnetic detection method" was proposed to realize rapid and flexible detection of pesticide residues on the surface of different foods including fish and apple. The limit of detection of malachite green and thiram on the fish and apple surfaces were 0.13 and 0.18 ng/cm2, respectively. With its high SERS performance and good magnetic, the DFAAA possessed great application prospects as a facile SERS substrate for rapid and non-destructive detection of trace pesticide residues on foods.

Reverse stable isotope labelling with Raman spectroscopy for microbial proteomics

Global proteome changes in microbes affect the survival and overall production of commercially relevant metabolites through different bioprocesses. The existing methods to monitor proteome level changes are destructive in nature. Stable isotope probing (SIP) coupled with Raman spectroscopy is a relatively new approach for proteome analysis. However, applying this approach for monitoring changes in a large culture volume is not cost-effective. In this study, for the first time we are presenting a novel method of combining reverse SIP using 13 C-glucose and Deuterium to monitor the proteome changes through Raman spectroscopy. The findings of the study revealed visible changes (blue shifts) in proteome related peaks that can be used for monitoring proteome dynamics, that is, synthesis of nascent amino acids and its turnover with time in a non-destructive, cost-effective, and label-free manner.

Fluorescent polythymidine-templated copper nanoclusters aptasensor for sensitive detection of tropomyosin in processed shrimp products

Tropomyosin (TM) is the main allergen in shellfish. Developing a novel, simple and accurate method to track and detect TM in food products is necessary. In this work, a label-free fluorescent aptasensor based on polythymidine (poly(T))-templated copper nanoclusters (CuNCs) was designed for sensitive detection of TM in processed shrimp products. Magnetic beads (MBs), aptamer and cDNA were used to construct an MBs-aptamer@cDNA complex as a detection probe, and with the presence of TM, the poly(T)-templated CuNCs attached at the end of the cDNA as the fluorescent signal was released from the complex to turn on the fluorescence. Under optimal conditions, the poly(T)-templated CuNCs aptasensor achieved a linear range from 0.1 to 50 μg/mL (R2 = 0.9980), a low limit of detection of 0.0489 μg/mL and an excellent recovery percentage of 105.29%-108.91% in the complex food matrix, providing a new approach for food safety assurance.

Dual-Stable-Isotope-Probed Raman microspectroscopy reveals the metabolic dynamic of Streptococcus mutans

Streptococcus mutans (S. mutans) is regarded as a cariogenic pathogen with the ability to metabolize sugars and form organic acids. However, its actual timely level of glucose consumption and cellular vitality in a polymicrobial culture system remains largely unknown. To tackle this challenge, we employed the S. mutans UA159 as a model and developed a dual-stable-isotope-probed Raman microspectroscopy method (Dual SIP-Raman) to simultaneously profile the general metabolic activity and glucose assimilative activity in situ. (i) Mono-SIP substrate feeding revealed that 0.5% 13C-glucose and 30% D2O were proper doses in the medium to obtain prominent and quantitative band shifts along with the 13C or D2O incorporation. In addition, the intensity of the 13C peak of phenylalanine (Phe) is proposed as a Raman-based biomarker for glucose utilization in a cell. (ii) The state of dual SIP substrate incorporation of 13C-glucose and D2O could be visualized by the corresponding spectral "red shifts" of Raman-scattered emissions; moreover, we also demonstrated that 13C/12C analysis was closely correlated with the C-D ratio. (iii) The application of the dual 13C-glucose and D2O feeding approach on a mock microbiota of S. mutans UA159 and C. albicans ATCC14053 revealed a stimulatory effect of fungus on both the glucose intake rate and general metabolic vitality of S. mutans UA159 (p < 0.05). Therefore, the 13C-glucose and D2O dual-feeding Raman Microspectroscopy approach is a valuable new tool for evaluating the glucose intake rate and general metabolic levels in situ, tracing the changing trend of the above metabolic activities, which is helpful to clarify the changes in the cariogenicity of oral microorganisms caused by the external environment at the single-cell level.

A three-dimensional gold nanoparticles spherical liquid array for SERS sensitive detection of pesticide residues in apple

High-performance plasmonic substrates have recently attracted much research attention. Herein, a three-dimensional gold nanoparticles (AuNPs) spherical liquid array (SLA) with high "hot spots" and tunable nanometer gap by optimizing the proportion of AuNPs colloids over chloroform was synthesized based on a water-oil interfacial self-assembly strategy. The substrate demonstrated excellent surface-enhanced Raman scattering (SERS) performance using tetrathiafulvalene and rhodamine 6G (R6G) as probe molecules. With a simple extraction and soaking pretreatment process, the SLA exhibited high sensitivity for analysing triazophos on apple peels, with a limit of detection (LOD) of 0.005 µg/mL and recovery ranging from 96 to 110 %. Particularly, the chloroform produced an inherent characteristic peak at 665 cm-1, which was used as the internal standard to correct SERS signal fluctuation, leading to an improvement of the corresponding coefficient R2 from 0.97 to 0.99, thus improving the reproducibility. Therefore the SLA substrate possesses the potential for quantitative analysis of food contaminants.

Non-Invasive Detection of Biomolecular Abundance from Fermentative Microorganisms via Raman Spectra Combined with Target Extraction and Multimodel Fitting

Biomolecular abundance detection of fermentation microorganisms is significant for the accurate regulation of fermentation, which is conducive to reducing fermentation costs and improving the yield of target products. However, the development of an accurate analytical method for the detection of biomolecular abundance still faces important challenges. Herein, we present a non-invasive biomolecular abundance detection method based on Raman spectra combined with target extraction and multimodel fitting. The high gain of the eXtreme Gradient Boosting (XGBoost) algorithm was used to extract the characteristic Raman peaks of metabolically active proteins and nucleic acids within E. coli and yeast. The test accuracy for different culture times and cell cycles of E. coli was 94.4% and 98.2%, respectively. Simultaneously, the Gaussian multi-peak fitting algorithm was exploited to calculate peak intensity from mixed peaks, which can improve the accuracy of biomolecular abundance calculations. The accuracy of Gaussian multi-peak fitting was above 0.9, and the results of the analysis of variance (ANOVA) measurements for the lag phase, log phase, and stationary phase of E. coli growth demonstrated highly significant levels, indicating that the intracellular biomolecular abundance detection was consistent with the classical cell growth law. These results suggest the great potential of the combination of microbial intracellular abundance, Raman spectra analysis, target extraction, and multimodel fitting as a method for microbial fermentation engineering.

A comprehensive review of microbial contamination in the indoor environment: sources, sampling, health risks, and mitigation strategies

The quality of the indoor environment significantly impacts human health and productivity, especially given the amount of time individuals spend indoors globally. While chemical pollutants have been a focus of indoor air quality research, microbial contaminants also have a significant bearing on indoor air quality. This review provides a comprehensive overview of microbial contamination in built environments, covering sources, sampling strategies, and analysis methods. Microbial contamination has various origins, including human occupants, pets, and the outdoor environment. Sampling strategies for indoor microbial contamination include air, surface, and dust sampling, and various analysis methods are used to assess microbial diversity and complexity in indoor environments. The review also discusses the health risks associated with microbial contaminants, including bacteria, fungi, and viruses, and their products in indoor air, highlighting the need for evidence-based studies that can relate to specific health conditions. The importance of indoor air quality is emphasized from the perspective of the COVID-19 pandemic. A section of the review highlights the knowledge gap related to microbiological burden in indoor environments in developing countries, using India as a representative example. Finally, potential mitigation strategies to improve microbiological indoor air quality are briefly reviewed.

Demonstrating low Raman background in UV-written SiO2 waveguides

Raman spectroscopy can give a chemical 'fingerprint' from both inorganic and organic samples, and has become a viable method of measuring the chemical composition of single biological particles. In parallel, integration of waveguides and microfluidics allows for the creation of miniaturized optical sensors in lab-on-a-chip devices. The prospect of combining integrated optics and Raman spectroscopy for Raman-on-chip offers new opportunities for optical sensing. A major limitation for this is the Raman background of the waveguide. This background is very low for optical fibers but remains a challenge for planar waveguides. In this work, we demonstrate that UV-written SiO2 waveguides, designed to mimic the performance of optical fibers, offer a significantly lower background than competing waveguide materials such as Si3N4. The Raman scattering in the waveguides is measured in absolute units and compared to that of optical fibers and Si3N4 waveguides. A limited study of the sensitivity of the Raman scattering to changes in pump wavelength and in waveguide design is also conducted. It is revealed that UV-written SiO2 waveguides offer a Raman background lower than -107.4 dB relative to a 785 nm pump and -106.5 dB relative to a 660 nm pump. Furthermore, the UV-written SiO2 waveguide demonstrates a 15 dB lower Raman background than a Si3N4 waveguide and is only 8.7 - 10.3 dB higher than optical fibers. Comparison with a polystyrene bead (in free space, diameter 7 µm) reveal an achievable peak SNR of 10.4 dB, showing the potential of UV-SiO2 as a platform for a Raman-on-chip device capable of measuring single particles.

Recent Progress in Screening of Mycotoxins in Foods and Other Commodities Using MXenes-Based Nanomaterials

Mycotoxin pollution in agricultural food products endangers animal and human health during the supply chains, therefore the development of accurate and rapid techniques for the determination of mycotoxins is of great importance for food safety guarantee. MXenes-based nanoprobes have attracted enormous attention as a complementary analysis and promising alternative strategies to conventional diagnostic methods, because of their fascinating features, like high electrical conductivity, various surface functional groups, high surface area, superb thermal resistance, good hydrophilicity, and environmentally-friendlier characteristics. In this study, we outline the state-of-the-art research on MXenes-based probes in detecting various mycotoxins like aflatoxin, ochratoxin, deoxynivalenol, zearalenone, and other toxins as a most commonly founded mycotoxin in the agri-food supply chain. First, we present the diverse synthesis approaches and exceptional characteristics of MXenes. Afterward, based on the detecting mechanism, we divide the biosensing utilizations of MXenes into two subcategories: electrochemical, and optical biosensors. Then their performance in effective sensing of mycotoxins is comprehensively deliberated. Finally, present challenges and prospective opportunities for MXenes are debated.

Preparation of Fe3O4@UiO-66(Zr)@Ag NPs core-shell-satellite structured SERS substrate for trace detection of organophosphorus pesticides residues

Surface-enhanced Raman spectroscopy (SERS) technology has been revived and developed with the introduction of metal-organic frameworks (MOFs), while more valuable properties of MOFs for SERS substrates remain largely unexplored. This work constructed a new SERS substrate Fe₃O₄@UiO-66(Zr)@Ag nanoparticles (FUAs) with excellent SERS detection sensitivity, uniformity, reproducibility and stability, exhibiting a high Raman enhancement factor (5.62 × 10⁶), low limit of detection (LOD, 2.11 × 10^-11 M) and RSD (12.41 %) for 4-NBT, and maintaining 81 % SERS activity within 60 days. The FUAs took full advantage of the strong affinity of UiO-66(Zr) for organophosphorus pesticides (OPs) to realize trace OPs detection. The LODs of phoxim, triazophos and methyl parathion in apple juice were 0.041, 0.021 and 0.0031 mg/L, respectively, with good linearities ranging from 0.02 or 0.1-50 mg/L, meeting the requirements of the food control standards, indicating that the potentials and prospects of the FUAs SERS substrate for trace detecting OPs in foods.

Process analytical technology as in-process control tool in semi-continuous manufacturing of PLGA/PEG-PLGA microspheres

Nowadays, among 3rd generation drug delivery systems, biodegradable polymeric based long-acting injectable depot has achieved tremendous success in clinical application. So far, there have been two dozen of commercial products of Poly (lactic-co-glycolic acid) microspheres available in the market. Recently, continuous manufacturing concept has been successfully applied on oral solid formulation from buzzword to reality. However, the polymeric injectable microspheres are still stayed at batch manufacturing phase due to the lack of understanding of knowledge matrix. In this study, micro-mixer as a plug-and-play emulsification modules, Raman spectroscopy and focused beam reflectance measurement as real-time monitoring modules are integrated into a novel semi-continuous manufacturing streamline to provides more efficient upscaling flexibility in microspheres production. In this end to end semi-continuous manufacturing process, amphiphilic block polymer monomethoxy-poly (ethylene glycol) modified PLGA (mPEG-PLGA) was used for encapsulating Gallic acid. Additionally, with guarantee of good robustness, the correlation relationship between critical process parameters, critical material attributes and critical quality attributes were investigated. The time-space evolution process and mechanism for formation of PEG-PLGA microsphere with particular morphology were elaborated. Altogether, this study firstly established semi-continuous manufacturing streamline for PLGA/PEG-PLGA microspheres, which would not only lower the cost of production, narrow process variability and smaller equipment/environmental footprint but also applied in-process control (IPC) and QbD principle on complicated production process of microspheres. Therefore, this study build confidence in the industrial development of PLGA/PEG-PLGA microspheres and establish best practice standards, which might be a quantum leap for developing PLGA microspheres in the future.

Distinguishing pericarpium citri reticulatae of different origins using terahertz time-domain spectroscopy combined with convolutional neural networks

The geographical indication of pericarpium citri reticulatae (PCR) is very important in grading the quality and price of PCRs. Therefore, terahertz time-domain spectroscopy (THz-TDS) technology combined with convolutional neural networks (CNN) was proposed to distinguish PCRs of different origins without damage in this study. The one-dimensional CNN (1D-CNN) model with an accuracy of 82.99% based on spectral data processed with SNV was established. The two-dimensional image features were transformed from unprocessed spectral data using the gramian angular field (GAF), the Markov transition field (MTF) and the recurrence plot (RP), which were used to build a two-dimensional CNN (2D-CNN) model with an accuracy of 78.33%. Further, the CNN models with different fusion methods were developed for fusing spectra data and image data. In addition, the adding spectra and images based on the CNN (Add-CNN) model with an accuracy of 86.17% performed better. Eventually, the Add-CNN model based on ten frequencies extracted using permutation importance (PI) achieved the identification of PCRs from different origins. Overall, the current study would provide a new method for identifying PCRs of different origins, which was expected to be used for the traceability of PCRs products.

Microfluidic single-cell scale-down systems: introduction, application, and future challenges

Performance losses during the scaling-up of bioprocesses from the laboratory to the production scale are common obstacles caused by the formation of concentration gradients in bioreactors. To overcome these obstacles, so-called scale-down bioreactors are used to analyze selected large-scale conditions and are one of the most important predictive tools for the successful transfer of bioprocesses from the lab to the industrial scale. In this regard, cellular behavior is usually measured as an averaged value, neglecting possible cell-to-cell heterogeneity within the culture. In contrast, microfluidic single-cell cultivation (MSCC) systems offer the possibility of understanding cellular processes on a single-cell level. To date, most MSCC systems have a limited choice of cultivation parameters that are not representative of bioprocess-relevant environmental conditions. Herein, we critically review recent advances in MSCC that allow the cultivation and analysis of cells under dynamic (bioprocess-relevant) environmental conditions. Finally, we discuss what technological advances and efforts are needed to bridge the gap between current MSCC systems and the use of these systems as single-cell scale-down devices.

Discrimination of Pericarpium Citri Reticulatae in different years using Terahertz Time-Domain spectroscopy combined with convolutional neural network

Pericarpium Citri Reticulatae (PCR) in longer storage years possess higher medicinal values, but their differentiation is difficult due to similar morphological characteristics. Therefore, this study investigated the feasibility of using terahertz time-domain spectroscopy (THz-TDS) combined with a convolutional neural network (CNN) to identify PCR samples stored from 1 to 20 years. The absorption coefficient and refractive index spectra in the range of 0.2-1.5 THz were acquired. Partial least squares discriminant analysis, random forest, least squares support vector machines, and CNN were used to establish discriminant models, showing better performance of the CNN model than the others. In addition, the output data points of the CNN intermediate layer were visualized, illustrating gradual changes in these points from overlapping to clear separation. Overall, THz-TDS combined with CNN models could realize rapid identification of different year PCRs, thus providing an efficient alternative method for PCR quality inspection.

Correlative Fluorescence and Raman Microscopy to Define Mitotic Stages at the Single-Cell Level: Opportunities and Limitations in the AI Era

Nowadays, morphology and molecular analyses at the single-cell level have a fundamental role in understanding biology better. These methods are utilized for cell phenotyping and in-depth studies of cellular processes, such as mitosis. Fluorescence microscopy and optical spectroscopy techniques, including Raman micro-spectroscopy, allow researchers to examine biological samples at the single-cell level in a non-destructive manner. Fluorescence microscopy can give detailed morphological information about the localization of stained molecules, while Raman microscopy can produce label-free images at the subcellular level; thus, it can reveal the spatial distribution of molecular fingerprints, even in live samples. Accordingly, the combination of correlative fluorescence and Raman microscopy (CFRM) offers a unique approach for studying cellular stages at the single-cell level. However, subcellular spectral maps are complex and challenging to interpret. Artificial intelligence (AI) may serve as a valuable solution to characterize the molecular backgrounds of phenotypes and biological processes by finding the characteristic patterns in spectral maps. The major contributions of the manuscript are: (I) it gives a comprehensive review of the literature focusing on AI techniques in Raman-based cellular phenotyping; (II) via the presentation of a case study, a new neural network-based approach is described, and the opportunities and limitations of AI, specifically deep learning, are discussed regarding the analysis of Raman spectroscopy data to classify mitotic cellular stages based on their spectral maps.

Analysis and detection using novel terahertz spectroscopy technique in dietary carbohydrate-related research: Principles and application advances

As one of the main functional substances, carbohydrates account for a large proportion of the human diet. Conventional analysis and detection methods of dietary carbohydrates and related products are destructive, time-consuming, and labor-intensive. In order to improve the efficiency of measurement and ensure food nutrition and consumer health, rapid and nondestructive quality evaluation techniques are needed. In recent years, terahertz (THz) spectroscopy, as a novel detection technology with dual characteristics of microwave and infrared, has shown great potential in dietary carbohydrate analysis. The current review aims to provide an up-to-date overview of research advances in using the THz spectroscopy technique in analysis and detection applications related to dietary carbohydrates. In the review, the principles of the THz spectroscopy technique are introduced. Advances in THz spectroscopy for quantitative and qualitative analysis and detection in dietary carbohydrate-related research studies from 2013 to 2022 are discussed, which include analysis of carbohydrate concentrations in liquid and powdery foods, detection of foreign body and chemical residues in carbohydrate food products, authentication of natural carbohydrate produce, monitoring of the fermentation process in carbohydrate food production and examination of crystallinity in carbohydrate polymers. In addition, applications in dietary carbohydrate-related detection research using other spectroscopic techniques are also briefed for comparison, and future development trends of THz spectroscopy in this field are finally highlighted.

Synthesis of recyclable SERS platform based on MoS2@TiO2@Au heterojunction for photodegradation and identification of fungicides

Surface-enhanced Raman spectroscopy (SERS) substrates based on metal/semiconductors have attracted much attention due to their excellent photocatalytic activity and SERS performance. However, they generally exhibit low light utilization and photocatalytic efficiencies. Herein, molybdenum disulfide coated titanium dioxide modified with gold nanoparticles (MoS₂@TiO₂@Au) as a heterojunction-based recyclable SERS platform was fabricated for the efficient determination of fungicides. Results showed that the MoS₂@TiO₂@Au platform could rapidly degrade 90.7% crystal violet in 120 min under solar light irradiation and enable reproducible and sensitive SERS analysis of three fungicides (methylene blue, malachite green, and crystal violet) and in-situ monitor of the photodegradation process. The platform could also be reused five times due to the unique integrated merits of the MoS₂@TiO₂@Au heterojunction. Meanwhile, experiments in determining methylene blue in prawn protein solution achieved a limit of detection of 1.509 μg/L. Therefore, it is hoped that this work could expand detection applications of photocatalytic materials.

Dry surface biofilms in the food processing industry: An overview on surface characteristics, adhesion and biofilm formation, detection of biofilms, and dry sanitization methods

Bacterial biofilm formation in low moisture food processing (LMF) plants is related to matters of food safety, production efficiency, economic loss, and reduced consumer trust. Dry surfaces may appear dry to the naked eye, however, it is common to find a coverage of thin liquid films and microdroplets, known as microscopic surface wetness (MSW). The MSW may favor dry surface biofilm (DSB) formation. DSB formation is similar in other industries, it occurs through the processes of adhesion, production of extracellular polymeric substances, development of microcolonies and maturation, it is mediated by a quorum sensing (QS) system and is followed by dispersal, leading to disaggregation. Species that survive on dry surfaces develop tolerance to different stresses. DSB are recalcitrant and contribute to higher resistance to sanitation, becoming potential sources of contamination, related to the spoilage of processed products and foodborne disease outbreaks. In LMF industries, sanitization is performed using physical methods without the presence of water. Although alternative dry sanitizing methods can be efficiently used, additional studies are still required to develop and assess the effect of emerging technologies, and to propose possible combinations with traditional methods to enhance their effects on the sanitization process. Overall, more information about the different technologies can help to find the most appropriate method/s, contributing to the development of new sanitization protocols. Thus, this review aimed to identify the main characteristics and challenges of biofilm management in low moisture food industries, and summarizes the mechanisms of action of different dry sanitizing methods (alcohol, hot air, UV-C light, pulsed light, gaseous ozone, and cold plasma) and their effects on microbial metabolism.

Antibiotic Susceptibility Testing with Raman Biosensing

Antibiotics guard us against bacterial infections and are among the most commonly used medicines. The immediate consequence of their large-scale production and prescription is the development of antibiotic resistance. Therefore, rapid detection of antibiotic susceptibility is required for efficient antimicrobial therapy. One of the promising methods for rapid antibiotic susceptibility testing is Raman spectroscopy. Raman spectroscopy combines fast and contactless acquisition of spectra with good selectivity towards bacterial cells. The antibiotic-induced changes in bacterial cell physiology are detected as distinct features in Raman spectra and can be associated with antibiotic susceptibility. Therefore, the Raman-based approach may be beneficial in designing therapy against multidrug-resistant infections. The surface-enhanced Raman spectroscopy (SERS) and resonance Raman spectroscopy (RRS) additionally provide excellent sensitivity. In this review, we present an analysis of the Raman spectroscopy-based optical biosensing approaches aimed at antibiotic susceptibility testing.

Visualization and quantification of content and hydrogen bonding state of water in apple and potato cells by confocal Raman microscopy: A comparison study

Water is the most abundant component in fresh fruit and vegetables and its distribution and hydrogen bonding state in cells has a significant influence on food processing. In the current study, an improved method based on our earlier studies was developed to directly visualize the spatial distribution of content and hydrogen bonding state of water in apple and potato cells for the first time and the difference in water distribution in these cells was compared. Additionally, based on the distribution images of content and hydrogen bonding state of water in different regions in apple and potato tissues, the total water and free water contents, and the hydrogen bonding state of free water were quantified and compared with those obtained by nuclear magnetic resonance and Marinchik methods, demonstrating that the method could be successfully used for quantifying the content and hydrogen bonding state of water in fruit and vegetable cells.

Analyzing macromolecular composition of E. Coli O157:H7 using Raman-stable isotope probing

Metabolic dynamics of bacterial cells is needed for understanding the correlation between changes in environmental conditions and cell metabolic activity. In this study, Raman spectroscopy combined with deuterium labelling was used to analyze the metabolic activity of a single Escherichia coli O157:H7 cell. The incorporation of deuterium from heavy water into cellular biomolecules resulted in the formation of carbon-deuterium (CD) peaks in the Raman spectra, indicating the cell metabolic activity. The broad vibrational peaks corresponding to CD and CH peaks encompassed different specific shifts of macromolecules such as protein, lipids, and nucleic acid. The utilization of tryptophan and oleic acid by the cell as the sole carbon source led to changes in cell lipid composition, as indicated by new peaks in the second derivative spectra. Thus, the proposed method could semi-quantitatively determine total metabolic activity, macromolecule specific identification, and lipid and protein metabolism in a single cell.

Detection of Bioactive Metabolites in Escherichia Coli Cultures Using Surface-Enhanced Raman Spectroscopy

Detection of bioactive metabolites produced by bacteria is important for identifying biomarkers for infectious diseases. In this study, a surface-enhanced Raman spectroscopy (SERS)-based technique was developed for the detection of bioactive metabolite indole produced by Escherichia coli (E. coli) in biological media. The use of highly sensitive Au@Ag core-shell nanoparticles resulted in the detection of indole concentration as low as 0.0886 mM in standard solution. The supplementation of growth media with 5 mM of exogenous tryptophan resulted in the production of a maximum yield of indole of 3.139 mM by E. coli O157:H7 at 37 °C. The growth of bacterial cells was reduced from 47.73 × 10⁸ to 1.033 × 10⁶ CFU/mL when the cells were grown in 0 and 10 mM exogenous tryptophan, respectively. The amount of indole in the Luria-Bertani (LB) media had an inverse correlation with the growth of cells, which resulted in a three-log reduction in the colony-forming unit when the indole concentration in the media was 20 times higher than normal. This work demonstrates that SERS is an effective and highly sensitive method for rapid detection of bioactive metabolites in biological matrix.

Perspectives and Trends in Advanced MXenes-Based Optical Biosensors for the Recognition of Food Contaminants

Fabricating novel biosensing constructs with high sensitivity and selectivity is highly demanded in food contaminants detection. In this prospect, various nanostructured materials were envisaged to build (bio)sensors with superior sensitivity and selectivity. The desirable biocompatibility, brilliant mechanical strength, ease of surface functionalization, as well as tunable optical and electronic features, portray 2D MXenes as versatile scaffolds for biosensing. In this review, we overviewed the state-of-the-art MXenes-based optical biosensing devices to detect mycotoxins, pesticide residues, antibiotic residues, and food borne-pathogens from foodstuff and environmental matrices. Firstly, the synthesis methods and surface functionalization/modification of MXenes are discussed. Secondly, according to the target analytes, we categorized and presented a detailed account of the newest research progress of MXenes-based optical probes for food contaminants monitoring. The efficiency of all the surveyed probes was assessed on the basis of important factors like response time, detection limit (DL), and sensing range. Lastly, the necessity and requirements for future advances in this emerging MXenes material are also given, followed by challenges and opportunities. We hope that this study will bridge the gap between nanotechnology and food science, offering insights for engineers or scientists in both areas to accelerate the progress of MXenes-based materials for food safety detection.

Living Sample Viability Measurement Methods from Traditional Assays to Nanomotion

Living sample viability measurement is an extremely common process in medical, pharmaceutical, and biological fields, especially drug pharmacology and toxicology detection. Nowadays, there are a number of chemical, optical, and mechanical methods that have been developed in response to the growing demand for simple, rapid, accurate, and reliable real-time living sample viability assessment. In parallel, the development trend of viability measurement methods (VMMs) has increasingly shifted from traditional assays towards the innovative atomic force microscope (AFM) oscillating sensor method (referred to as nanomotion), which takes advantage of the adhesion of living samples to an oscillating surface. Herein, we provide a comprehensive review of the common VMMs, laying emphasis on their benefits and drawbacks, as well as evaluating the potential utility of VMMs. In addition, we discuss the nanomotion technique, focusing on its applications, sample attachment protocols, and result display methods. Furthermore, the challenges and future perspectives on nanomotion are commented on, mainly emphasizing scientific restrictions and development orientations.

Novel graphene oxide/polymer composite membranes for the food industry: structures, mechanisms and recent applications

The membrane can not only be used as food packaging, but also for the separation, fractionation and recovery of food ingredients. Graphene oxide (GO) sheets are a two-dimensional (2 D) material with a unique structure that exhibit excellent mechanical properties, biocompatibility, and flexibility. The corporation of polymer matrix membrane with GO can significantly improve the permeability, selectivity, and antibacterial activity. In this review, the chemical structures of GO, GO membranes and GO/polymer composite membranes are introduced, the permeation mechanisms of molecules through the membranes are discussed and key factors affecting the permeability are presented in detail. In addition, recent applications in the food industry for filtration, bioreactions and active food packaging are analyzed, and limitations and future trends of GO membranes development are also highlighted. GO/polymer composite membranes exhibit excellent permeability, selectivity and strong barrier properties against bacterial and gas permeation. However, current food material filtration and packaging applications of GO/polymer composite membranes are still in the laboratory stage. Future work can focus on the development of large scale uniformly sized GO production, the homogeneous distribution and tight combination of GO in polymer matrixes, the sensing function of GO in packaging, and the verification method of GO toxicology.

Interfacing metal-polyphenolic networks upon photothermal gold nanorods for triplex-evolved biocompatible bactericidal activity

Gold nanorods (GNRs) outstand in photothermal disinfection but are faced with severe surface chemistry and dose relevant biotoxicity. Herein, a naturally green building block, metal-phenolic networks (MPNs), was employed to functionalize GNRs via coordination reaction, yielding a tunable and biocompatible core-shell photothermal nano-bactericide (GNRs@MPNs). The bioactive GNRs@MPNs built with iron and polyphenols (tannic acid, epigallocatechin gallate, and procyanidins) exhibited superior light-to-heat conversion efficiencies with η = 29.29-44.00%, remarkably preceding that of GNRs (η = 12.24%), which could rapidly ablate 99.8% of Escherichia coli O157: H7 and 98.6% of Staphylococcus aureus bacteria in relatively low efficacy doses (10 ppm of Au). Moreover, local heat triggered by GNRs@MPNs accelerated the healing of the cutaneous wound of a mice model infected by methicillin-resistant S. aureus. The facile synthesis, photothermal synergy, polyphenolic bioactivity, and significantly low efficacy dose of GNRs@MPNs empower them satisfactory efficiency and biosafety in the future broad-spectrum photothermal sterilization applications.

Ti3C2Tx MXenes loaded with Au nanoparticle dimers as a surface-enhanced Raman scattering aptasensor for AFB1 detection

Mycotoxin B1 (AFB1) contamination in agricultural products pose a deadlydangertoanimal and human health and its rapid and reliable detection is thus very important. Herein, a ratiometric surface-enhanced Raman scattering (SERS) aptasensor for AFB1 detection was developed, in which 1,2-bis(4-pyridyl) ethylene (BPE) was used to trigger the assembly of Au nanoparticle dimers (AuNP dimers) and form intensive SERS "hot spots", and MXenes nanosheets could load aptamer-modified AuNP dimers due to the hydrogen bonding and the chelation between the phosphate groups of aptamers and the Ti ion of MXenes. With the presence of AFB1 preferentially binding to AFB1 aptamer, AuNP dimers were separated from MXenes nanosheets, leading to a decrease in SERS intensity. Regression analysis in the range from 0.001 to 100 ng·mL^-1 showed the limit of detection (LOD) being 0.6 pg·mL^-1 in standard solution, indicating that the great prospects of the AuNP dimers/MXenes SERS substrate for detecting AFB1.

Machine Learning-Driven Multiobjective Optimization: An Opportunity of Microfluidic Platforms Applied in Cancer Research

Cancer metastasis is one of the primary reasons for cancer-related fatalities. Despite the achievements of cancer research with microfluidic platforms, understanding the interplay of multiple factors when it comes to cancer cells is still a great challenge. Crosstalk and causality of different factors in pathogenesis are two important areas in need of further research. With the assistance of machine learning, microfluidic platforms can reach a higher level of detection and classification of cancer metastasis. This article reviews the development history of microfluidics used for cancer research and summarizes how the utilization of machine learning benefits cancer studies, particularly in biomarker detection, wherein causality analysis is useful. To optimize microfluidic platforms, researchers are encouraged to use causality analysis when detecting biomarkers, analyzing tumor microenvironments, choosing materials, and designing structures.

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.

A dual AE-GAN guided THz spectral dehulling model for mapping energy and moisture distribution on sunflower seed kernels

Energy and moisture contents are important food chemical attributes. In the current study, a nondestructive Terahertz (THz) time-domain imaging system was first time used for evaluating the energy and moisture distributions of sunflower seed kernels inside shells. For this task, a dual autoencoders (AE)-generative adversarial nets (GAN) spectral dehulling semi-supervised model was developed. The model could automatically learn the kernel information from the latent representations of the spectra of the intact seeds through adversarial learning to achieve feature disentanglement. Results indicated that the generated kernel images had similar features to the original kernel images and high-quality chemical distribution maps for energy and moisture contents of sunflower seed kernels inside shells were successfully obtained. As the current method took the advantage of the characteristics of THz imaging and selected a suitable deep learning algorithm, it has the potential to generalize for imaging other chemical substances of other dry shelled seeds or biological samples (moisture content and thickness below 15% and 5 mm, respectively).

Precision release systems of food bioactive compounds based on metal-organic frameworks: synthesis, mechanisms and recent applications

Controlled release (CR) systems have become a powerful platform for accurate and effective delivery of bioactive compounds (BCs). Metal-organic frameworks (MOFs) are one of the best BCs-loaded carriers for CR systems. In the review, the principles and methods of the design and synthesis of MOFs-CR systems are summarized in detail, the encapsulation of BCs by MOFs and CR mechanisms are explored, and their biological toxicity and biocompatibility are highlighted and applications in the food industry are discussed. In addition, current challenges in this field and possible future development directions are also presented. MOFs have been proven to encapsulate BCs effectively, including gaseous and solid molecules, and control the release of BCs through spontaneous diffusion or stimulus-response. The solubility, stability and biocompatibility of BCs encapsulated by MOFs are greatly improved, which expands their applications in foods. The effective CR of BCs by MOFs-CR systems is beneficial to assist in maintaining or even improving the quality and safety of food, reduce the BCs usage while increasing the bioavailability. Low- or non-biotoxic MOFs, especially bio-MOFs, show greater application prospects in the food industry.

Bio-Specific Au/Fe3+ Porous Spongy Nanoclusters for Sensitive SERS Detection of Escherichia coli O157:H7

For sensitive and fast detection of Escherichia coli O157:H7, organic and inorganic hybrid Au/Fe³⁺ nanoclusters (NCs) were synthesized for the first time using gold nanoparticles (GNPs), bovine serum albumin, ferric chloride, phosphate-buffered saline, and antibodies. The Au/Fe³⁺ porous spongy NCs with large surface area showed excellent bio-specific capability for E. coli O157:H7. GNPs in Au/Fe³⁺ NCs functioned as signal enhancers, significantly increasing the Raman signal via the metathesis reaction product of Prussian blue and obviously improving the detection sensitivity. We combined the novel Au/Fe³⁺ NCs with antibody-modified magnetic nanoparticles to create a biosensor capable of sensitive detection of E. coli O157:H7, which showed a good linear response (10¹ to 10⁶ cfu/mL), high detection sensitivity (2 cfu/mL), and good recovery rate (93.60–97.50%) in spiked food samples. These results make the biosensor well-suited for food safety monitoring. This strategy achieves the goal of sensitive and quantitative detection of E. coli O157:H7.