Advances in microbial analysis: based on volatile organic compounds of microorganisms in food

Comparative transcriptomic analysis and volatile compound characterization of Aspergillus tubingensis and Penicillium oxalicum during their infestation of Japonica rice

Volatile organic compounds (VOCs), a byproduct of mold metabolism, have garnered increasing interest because the VOCs can be used to detect food early contamination. So far, the use of VOCs as indicators of rice mildew, specifically caused by Aspergillus tubingensis and Penicillium oxalicum, and the mechanisms of their generation are not well investigated. This study examines the VOCs produced by these molds during paddy storage, utilizing headspace solid-phase micro-extraction gas chromatography-mass spectrometry (HS-SPME-GC-MS). We further elucidate the mechanisms underlying the formation of these VOCs through a comparative transcriptomic analysis. The VOCs characteristic to A. tubingensis and P. oxalicum, identified with a VIP value > 1 in the partial least squares discriminant analysis (PLS-DA) model, are primarily alkenes. Our transcriptome analysis uncovers key metabolic pathways in both molds, including energy metabolism and pathways related to volatile substance formation, and identifies differentially expressed genes associated with alkane and alcohol formation.

Moldy odors in food - a review

Food products are susceptible to mold contamination, releasing moldy odors. These moldy odors not only affect the flavor of food, but also pose a risk to human health. Moldy odors are a mixture of volatile organic compounds (VOCs) released by the fungi themselves, which are the main source of moldy odors in moldy foods. These VOCs are secondary metabolites of fungi and are synthesized through various biosynthetic pathways. Both the fungi themselves and environmental factors affect the release of moldy odors. This review summarized the main components of musty odors in moldy foods and their producing fungi. In addition, this review focused on the functions of moldy volatile organic compounds (MVOCs) and the biosynthetic pathways of the major MVOCs, and summarized the factors affecting the release of MVOCs as well as the detection methods. It expected to provide a basis for ensuring food safety.

Identification of Potential Biomarkers and Spectral Fingerprinting for Detection of Foodborne Pathogens in Raw Chicken Meat Matrix Using GCMS and FTIR

Foodborne illnesses pose a serious threat to public health, with increasing global incidence rates driven by factors such as rising meat consumption. Rapid detection of foodborne pathogens in meat is critical for preventing outbreaks. This study investigates the potential of gas chromatography-mass spectrometry (GC-MS) and Fourier-transform infrared spectroscopy (FTIR) for identifying biomarkers and spectral fingerprints indicative of foodborne pathogens in raw chicken meat. Raw broiler chicken meat samples were surface-sterilized and inoculated with foodborne pathogens. The samples were challenge inoculated with the specific pathogen and the physical quality parameters like pH, color, texture, drip loss, and water activity were assessed. GC-MS analysis identified 113 metabolites, including potential biomarkers like ureidopropionic acid, 5-sulfosalicylic acid, 11,14-eicosadienoic acid, methyl ester for E. coli O157:H7; 11-bromoundecanoic acid, neocurdione, glafenin, eicosanoic acid for Salmonella; azepan-1-yl-acetic acid, methyl ester, tramadol, cytarabine, dipipanone for Staphylococcus and cyclopentaneundecanoic acid, phosphonofluoridic acid, î-n-formyl-l-lysine for Pseudomonas. Pathway analysis revealed the involvement of fatty acid metabolism and amino acid degradation pathways. FTIR spectral data showed significant variances between control and spiked samples, particularly in the fatty acid spectral region. The identified metabolites and spectral patterns could serve as biomarkers for developing rapid pathogen detection methods, contributing to enhanced food safety protocols.

Controlling soft rot of green pepper by bacteriocin paracin wx3 and its effect on storage quality of green pepper

A bacteriocin paracin wx3 was investigated as a candidate of natural preservative to control green pepper soft rot. Firstly, paracin wx3 was heterologously expressed in Pichia pastoris X33 with an improved yield of 0.537 g/L. Its size and amino acid sequence were confirmed by Tricine-SDS-PAGE and LC-MS/MS. Then, result of antibacterial activity showed that its MIC value against Pectobacterium carotovorum was 16 μg/mL. In vitro, paracin wx3 completely killed the pathogen at high concentrations ≥8 × MIC. In vivo, disease incidence of green pepper soft rot was decreased from 90% (control) to <2% (8 × MIC). Subsequently, results of action mode showed that paracin wx3 inhibited the growth of pathogen by pore-formation on cell membrane. Last, paracin wx3 treatment reduced losses of weight, firmness, total soluble solid, Vc of green pepper during storage. It also inhibited the production of soft rot volatile p-xylene, 1-butanol, 2-methyl-2-propanol, 3-hydroxybutan-2-one-D, 2-pentyl furan, butanal, etc.

Unveiling the hidden impact: How biodegradable microplastics influence CO2 and CH4 emissions and Volatile Organic Compounds (VOCs) profiles in soil ecosystems

Biodegradable plastics promise eco-friendliness, yet their transformation into microplastics (bio-MPs) raises environmental alarms. However, how those bio-MPs affect the greenhouse gases (GHGs) and volatile organic compounds (VOCs) in soil ecosystems remains largely unexplored. Here, we investigated the effects of diverse bio-MPs (PBAT, PBS, and PLA) on GHGs and VOCs emission in typical paddy or upland soils. We monitored the carbon dioxide (CO2) and methane (CH4) fluxes in-situ using the self-developed portable optical gas sensor and analyzed VOC profiles using a proton-transfer reaction mass spectrometer (PTR-MS). Our study has revealed that, despite their biodegradable nature, bio-MPs do not always promote soil GHG emissions as previously thought. Specifically, PBAT and PLA significantly increased CO2 and CH4 emissions up to 1.9-7.5 and 115.9-178.5 fold, respectively, compared to the control group. While PBS exhibited the opposite trend, causing a decrease of up to 39.9% for CO2 and up to 39.9% for CH4. In addition, different types of bio-MPs triggered distinct soil VOC emission patterns. According to the Mann-Whitney U-test and Partial Least Squares Discriminant Analysis (PLS-DA), a recognizable VOC pattern associated with different bio-MPs was revealed. This study claims the necessity of considering polymer-specific responses when assessing the environmental impact of Bio-MPs, and providing insights into their implications for climate change.

Characteristic volatiles of Fu brick tea formed primarily by extracellular enzymes during Aspergillus cristatus fermentation

Fu brick tea (FBT) has unique "fungal flower" aroma traits, but its source of crucial aroma compounds is still controversial. Aspergillus cristatus is the dominant fungus that participated in the fermentation of FBT. In this study, volatiles of Aspergillus cristatus and corresponding fermented FBT were examined using GC × GC-Q-TOFMS. A total of 59 volatiles were shared by three strains of Aspergillus cristatus isolated from representative FBT. Among them, 1-octen-3-ol and 3-octanone were the most abundant. A total of 133 volatiles were screened as typical FBT volatiles from three FBTs fermented by the corresponding fungi. Aspergillus cristatus and FBT had only 29 coexisting volatiles, indicating that the volatiles of Aspergillus cristatus could not directly contribute to the aroma of FBT. The results of no significant correlation between volatile content in FBT and volatile content in Aspergillus cristatus suggested that intracellular metabolism of Aspergillus cristatus was not a direct driver of FBT aroma formation. Metabolic pathway analysis and proteomic analysis showed that the aroma in FBT was mainly formed by the enzymatic reaction of extracellular enzymes from Aspergillus cristatus. This study enriched our understanding of Aspergillus cristatus in the aroma formation process of FBT.

Two-Dimensional SERS Sensor Array for Identifying and Visualizing the Gas Spatial Distributions of Two Distinct Odor Sources

The spatial distribution of gas emitted from an odor source provides valuable information regarding the composition, size, and localization of the odor source. Surface-enhanced Raman scattering (SERS) gas sensors exhibit ultra-high sensitivity, molecular specificity, rapid response, and large-area detection. In this paper, a SERS gas sensor array was developed for visualizing the spatial distribution of gas evaporated from benzaldehyde and 4-ethylbenzaldehyde odor sources. The SERS spectra of the gas were collected by scanning the sensor array using an automatic detection system. The non-negative matrix factorization algorithm was employed to extract feature and concentration information at each spot on the sensor array. A heatmap image was generated for visualizing the gas spatial distribution using concentration information. Gaussian fitting was applied to process the image for localizing the odor source. The size of the odor source was estimated using the processed image. Moreover, the spectra of benzaldehyde, 4-ethylbenzaldehyde, and their gas mixture were simultaneously detected using one SERS sensor array. The feature information was recognized using a convolutional neural network with an accuracy of 98.21%. As a result, the benzaldehyde and 4-ethylbenzaldehyde odor sources were identified and visualized. Our research findings have various potential applications, including odor source localization, environmental monitoring, and healthcare.

Volatile compounds produced in smoked bacon inoculated with potential spoilage bacteria

BACKGROUND

Volatile organic compounds (VOCs) produced during meat storage are mainly derived from the decomposition of meat components and the metabolism of spoilage bacteria. VOCs produced in sterile bacon model substrate inoculated or un-inoculated with spoilage bacteria, Staphylococcus xylosus (P2), Leuconostoc mesenteroides (P6), Carnobacterium maltaromaticum (P9), Leuconostoc gelidum (P16) and Serratia liquefaciens (P20), previously isolated, were identified by headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). Furthermore, combinations of the strains (Pm) were also obtained.

RESULTS

In total, 54 volatile compounds, including aldehydes, alcohols, phenols, ketones, alkanes, alkanes, organic acids, esters and so forth, were determined after 45 days of storage in bacon inoculated with potential spoilage bacteria using the HS-SPME/GC-MS method. VOC concentrations of alcohols and organic acids in groups inoculated with bacteria were remarkably higher (P < 0.05) compared to that in control samples. Specifically, some VOCs are closely related to the metabolic activity of the inoculated bacterial strains; for example, 2,3-butanediol was associated with P2, P16 and P20, and acetic acid was mainly related to P6 and P9.

CONCLUSION

The results of partial least squares regression indicated that there was a high correlation between the electronic nose sensors and VOCs of smoked inoculated potential spoilage bacteria. These compounds are potentially important for predicting deterioration of smoked bacon. © 2023 Society of Chemical Industry.

Consumer-oriented smart dynamic detection of fresh food quality: recent advances and future prospects

Since fresh foods include a significant amount of water, fat, and protein, it is more likely to become infected by microorganisms causing a major loss of quality. Traditional detection techniques are less able to meet customer expectations owing to the limitations of high cost, slow response time, and inability to permit dynamic monitoring. Intelligent non-destructive detection technologies have emerged in recent years, which offer the advantages of small size and fast response at low cost. However, dynamic monitoring of fresh food quality based on intelligent detection technologies on the consumer side has not been rigorously evaluated yet. This paper discussed the application of intelligent detection technologies based on the consumer side in the dynamic monitoring of fresh food freshness, microorganisms, food additives, and pesticide residues. Furthermore, the application of intelligent detection technologies combined with smartphones for quality monitoring and detection of fresh foods is evaluated. Moreover, the challenges and development trends of intelligent fresh food quality detection technologies are also discussed. Intelligent detection technologies based on the consumer side are designed to detect in real-time the quality of fresh food through visual color changes in combination with smartphones. This paper provides ideas and recommendations for the application of intelligent detection technologies based on the consumer side in food quality detection/monitoring and future research trends.