GC-MS Based Metabolomics for Rapid Simultaneous Detection of Escherichia coli O157:H7, Salmonella Typhimurium, Salmonella Muenchen, and Salmonella Hartford in Ground Beef and Chicken

Identification of metabolite biomarkers in Salmonella enteritidis-contaminated chickens using UHPLC-QTRAP-MS-based targeted metabolomics

This study aimed to characterize the metabolic profile of Salmonella enteritidis (S. enteritidis) in chicken matrix and to identify metabolic biomarkers of S. enteritidis in chicken. The UHPLC-QTRAP-MS high-throughput targeted metabolomics approach was employed to analyze the metabolic profiles of contaminated and control group chickens. A total of 348 metabolites were quantified, and the application of deep learning least absolute shrinkage and selection operator (LASSO) modelling analysis obtained eight potential metabolite biomarkers for S. enteritidis. Metabolic abundance change analysis revealed significantly enriched abundances of anthranilic acid, l-pyroglutamic acid, 5-hydroxylysine, n,n-dimethylarginine, 4-hydroxybenzoic acid, and menatetrenone in contaminated chicken samples. The receiver operating characteristic (ROC) curve analysis demonstrated the strong ability of these six metabolites as biomarkers to distinguish S. enteritidis contaminated and fresh chicken samples. The findings presented in this study offer a theoretical foundation for developing an innovative approach to identify and detect foodborne contamination caused by S. enteritidis.

Untargeted and targeted metabolomics identify metabolite biomarkers for Salmonella enteritidis in chicken meat

Salmonella Enteritidis easily contaminate chicken during slaughtering, processing, transportation, and sales, which seriously endangers human health. This study aimed to identify metabolite biomarkers for Salmonella Enteritidis contamination in chicken meat. UPLC-Q-Orbitrap MS untargeted metabolomics analysis identified 441 and 240 confidently metabolites in positive and negative ion mode, respectively. Thirty metabolites were defined as potential biomarkers for Salmonella enteritidis contamination in chicken meat. UPLC-QQQ-MS based targeted metabolomics was used to quantitatively analyze candidate metabolite biomarkers in Salmonella enteritidis contaminated and fresh chicken samples. A total of 10 candidate metabolite biomarkers were confirmed in the validation set, among which acetylcholine, l-Methionine, l-Proline, l-Valine, and l-Norleucine were identified as biomarkers for Salmonella Enteritidis contamination in chicken. The combined receiver operating characteristic curve analysis of the five biomarkers achieved an AUC of 0.956, indicating their high sensitivity and specificity in predicting Salmonella Enteritidis in raw chicken. In conclusion, the present study identified five metabolite biomarkers for Salmonella enteritidis in raw chicken. These results provide a potential theoretical basis for developing Salmonella Enteritidis detection methods in raw chicken.

Bacillus subtilis DSM29784 attenuates Clostridium perfringens-induced intestinal damage of broilers by modulating intestinal microbiota and the metabolome

Necrotic enteritis (NE), especially subclinical NE (SNE), without clinical symptoms, in chicks has become one of the most threatening problems to the poultry industry. Therefore, increasing attention has been focused on the research and application of effective probiotic strains as an alternative to antibiotics to prevent SNE in broilers. In the present study, we evaluated the effects of Bacillus subtilis DSM29784 (BS) on the prevention of subclinical necrotic enteritis (SNE) in broilers. A total of 480 1-day-old broiler chickens were randomly assigned to four dietary treatments, each with six replicates pens of twenty birds for 63 d. The negative (Ctr group) and positive (SNE group) groups were only fed a basal diet, while the two treatment groups received basal diets supplemented with BS (1 × 109 colony-forming units BS/kg) (BS group) and 10mg/kg enramycin (ER group), respectively. On days 15, birds except those in the Ctr group were challenged with 20-fold dose coccidiosis vaccine, and then with 1 ml of C. perfringens (2 × 108) at days 18 to 21 for SNE induction. BS, similar to ER, effectively attenuated CP-induced poor growth performance. Moreover, BS pretreatment increased villi height, claudin-1 expression, maltase activity, and immunoglobulin abundance, while decreasing lesional scores, as well as mucosal IFN-γ and TNF-α concentrations. In addition, BS pretreatment increased the relative abundance of beneficial bacteria and decreased that of pathogenic species; many lipid metabolites were enriched in the cecum of treated chickens. These results suggest that BS potentially provides active ingredients that may serve as an antibiotic substitute, effectively preventing SNE-induced growth decline by enhancing intestinal health in broilers.

Rapid detection of Escherichia coli in dairy milk using static headspace-comprehensive two-dimensional gas chromatography

A new approach is introduced for rapid and reliable bacteria detection in food. Namely, static headspace-comprehensive two-dimensional gas chromatography (HS-GC × GC) with backflushing. The introduced approach provides fast detection of Escherichia coli (E. coli) in enriched ultra-high-temperature processed (UHT) dairy milk. The presence of E. coli may be indicated by detecting microbial volatile organic compounds emanating from test solutions inoculated with E. coli. In the present investigation, HS-GC × GC analysis is preceded by conventional enrichment in nutrient broth and inoculated samples are clearly discernable from controls following as little as 15 h sample enrichment. Headspace equilibration for 28 min followed by an 8 min GC × GC analysis of enriched test solutions reduces time-to-response by approximately one full day compared to conventional culture-based methods. The presence of ethanol, 1-propanol, and acetaldehyde may be used as a putative marker of E. coli contamination in milk and the introduced approach is able to detect single-cell initial bacterial load. Faster, reliable detection of pathogens and/or spoilage microbes in food products is desirable for the food industry. The described approach has great potential to complement the conventional workflow and be utilised for rapid microbial screening of foodstuff.

A cerumenolomic approach to bovine trypanosomosis diagnosis

INTRODUCTION

Trypanosomiasis caused by Trypanosoma vivax (T. vivax, subgenus Duttonella) is a burden disease in bovines that induces losses of billions of dollars in livestock activity worldwide. To control the disease, the first step is identifying the infected animals at early stages. However, convention tools for animal infection detection by T. vivax present some challenges, facilitating the spread of the pathogenesis.

OBJECTIVES

This work aims to develop a new procedure to identify infected bovines by T. vivax using cerumen (earwax) in a volatilomic approach, here named cerumenolomic, which is performed in an easy, quick, accurate, and non-invasive manner.

METHODS

Seventy-eight earwax samples from Brazilian Curraleiro Pé-Duro calves were collected in a longitudinal study protocol during health and inoculated stages. The samples were analyzed using Headspace/Gas Chromatography-Mass Spectrometry followed by multivariate analysis approaches.

RESULTS

The cerumen analyses lead to the identification of a broad spectrum of volatile organic metabolites (VOMs), of which 20 VOMs can discriminate between healthy and infected calves (AUC = 0.991, sensitivity = 0.967, specificity = 1.000). Furthermore, 13 VOMs can indicate a pattern of discrimination between the acute and chronic phases of the T. vivax infection in the animals (AUC = 0.989, sensitivity = 0.944, specificity = 1.000).

CONCLUSION

The cerumen volatile metabolites present alterations in their occurrence during the T.vivax infection, which may lead to identifying the infection in the first weeks of inoculation and discriminating between the acute and chronic phases of the illness. These results may be a breakthrough to avoid the T. vivax outbreak and provide a faster clinical approach to the animal.

Rapid and Multiplexed Detection of Single Cells of Salmonella, Escherichia coli O157, and Shigella flexneri in Ground Beef by Flow Cytometry

Salmonella, Escherichia coli O157, and Shigella flexneri are typical foodborne pathogens in ground beef, which can cause severe infection even when present as a single cell. Flow cytometry (FCM) methods are widely applied in the rapid detection of pathogens in food products. In this study, we report an FCM-based method for detecting single cells of Salmonella, E. coli O157, and S. flexneri in 25 g ground beef samples. We fluorescently labeled specific antibodies that could effectively identify bacterial cells, prepared single-cell samples by serial dilution, and optimized the pre-enrichment time. The results showed that 7 h of pre-enrichment is appropriate for sensitive single-cell detection by FCM. Finally, we evaluated this method in artificially contaminated and retail beef samples. This study outlines a novel highly sensitive FCM-based method to detect Salmonella, E. coli O157, and S. flexneri in beef samples within 8 h that can be applied to the rapid and multiplexed detection of foodborne pathogens.

Rapid and multiplexed quantification of Salmonella, Escherichia coli O157:H7, and Shigella flexneri in ground beef using flow cytometry

Salmonella, Escherichia coli O157:H7 (E. coli O157:H7) and Shigella flexneri (S. flexneri) might contaminate similar types of meat products and cause deadly diseases in humans. In reality, ground beef samples may carry more than one pathogen and a rapid and accurate detection method for the simultaneous identification of multiple specific pathogenic strains in ground beef is crucial. In this study, a sample pretreatment protocol and a flow cytometry method were developed for rapid and multiplexed quantification of the three pathogens without cultural enrichment in ground beef. The whole process of sample pretreatment, staining, and instrument analysis can be accomplished within 1 h. The three bacteria upon sample pretreatment were demonstrated good recoveries (93.8%-101.2%). The quantitative detection range of the mothed was 10³ to 10⁸ cells/g for all three pathogens, and the detection limit for Salmonella, E. coli O157:H7 and S. flexneri in ground beef were 3.1 × 10³ cells/g, 2.1 × 10³ cells/g and 2.3 × 10³ cells/g, respectively. Therefore, the as-developed approach is a rapid and quantitative method for multiplexed detection of Salmonella, E. coli O157:H7, and S. flexneri in ground beef.

Volatile Nitrogenous Compounds from Bacteria: Source of Novel Bioactive Compounds

Bacteria can produce nitrogenous compounds via both primary and secondary metabolic processes. Many bacterial volatile nitrogenous compounds produced during the secondary metabolism have been identified and reported for their antioxidant, antibacterial, antifungal, algicidal and antitumor activities. The production of these nitrogenous compounds depends on several factors, including the composition of culture media, growth conditions, and even the organic solvent used for their extraction, thus requiring their identification in specific conditions. In this review, we describe the volatile nitrogenous compounds produced by bacteria especially focusing on their antimicrobial activity. We concentrate on azo-compounds mainly pyrazines and pyrrolo-pyridines reported for their activity against several microorganisms. Whenever significant, extraction and identification methods of these compounds are also mentioned and discussed. To the best of our knowledge, this is first review describing volatile nitrogenous compounds from bacteria focusing on their biological activity.

Nondestructive multiplex detection of foodborne pathogens with background microflora and symbiosis using a paper chromogenic array and advanced neural network

We have developed an inexpensive, standardized paper chromogenic array (PCA) integrated with a machine learning approach to accurately identify single pathogens (Listeria monocytogenes, Salmonella Enteritidis, or Escherichia coli O157:H7) or multiple pathogens (either in multiple monocultures, or in a single cocktail culture), in the presence of background microflora on food. Cantaloupe, a commodity with significant volatile organic compound (VOC) emission and large diverse populations of background microflora, was used as the model food. The PCA was fabricated from a paper microarray via photolithography and paper microfluidics, into which 22 chromogenic dye spots were infused and to which three red/green/blue color-standard dots were taped. When exposed to VOCs emitted by pathogens of interest, dye spots exhibited distinguishable color changes and pattern shifts, which were automatically segmented and digitized into a ΔR/ΔG/ΔB database. We developed an advanced deep feedforward neural network with a learning rate scheduler, L₂ regularization, and shortcut connections. After training on the ΔR/ΔG/ΔB database, the network demonstrated excellent performance in identifying pathogens in single monocultures, multiple monocultures, and in cocktail culture, and in distinguishing them from the background signal on cantaloupe, providing accuracy of up to 93% and 91% under ambient and refrigerated conditions, respectively. With its combination of speed, reliability, portability, and low cost, this nondestructive approach holds great potential to significantly advance culture-free pathogen detection and identification on food, and is readily extendable to other food commodities with complex microflora.

Metabolomic approaches for the determination of metabolites from pathogenic microorganisms: A review

Metabolomics is a high precision analytical approach to obtaining detailed information of varieties of metabolites produced in biological systems, including foods. This study reviews the use of metabolomic approaches such as liquid chromatography mass spectrometry (LCMS), gas chromatography mass spectrometry (GC-MS), matrix assisted laser desorption /ionization tandem time of flight mass spectrometry (MALDI-TOF-MS) and nuclear magnetic resonance (NMR) for investigating the presence of foodborne pathogens and their metabolites. Pathogenic fungi and their notable metabolites (mycotoxins) have been studied more extensively using metabolomics as compared to bacteria, necessitating further studies in this regard. Nevertheless, such identified fungal and bacteria metabolites could be used as biomarkers for a more rapid detection of these pathogens in food. Other important compounds detected through metabolomics could also be correlated to functionality of these pathogenic strains, determined by the composition of the foods in which they exist, thereby providing insights into their metabolism. Considering the prevalence of these food pathogens, metabolomics still has potentials in the determination of food-borne pathogenic microorganisms especially for the determination of pathogenic bacteria toxins and is expected to generate research interests for further studies and applications.

Utilizing the Food-Pathogen Metabolome to Putatively Identify Biomarkers for the Detection of Shiga Toxin-Producing E. coli (STEC) from Spinach

Shiga toxigenic E. coli (STEC) are an important cause of foodborne disease globally with many outbreaks linked to the consumption of contaminated foods such as leafy greens. Existing methods for STEC detection and isolation are time-consuming. Rapid methods may assist in preventing contaminated products from reaching consumers. This proof-of-concept study aimed to determine if a metabolomics approach could be used to detect STEC contamination in spinach. Using untargeted metabolic profiling, the bacterial pellets and supernatants arising from bacterial and inoculated spinach enrichments were investigated for the presence of unique metabolites that enabled categorization of three E. coli risk groups. A total of 109 and 471 metabolite features were identified in bacterial and inoculated spinach enrichments, respectively. Supervised OPLS-DA analysis demonstrated clear discrimination between bacterial enrichments containing different risk groups. Further analysis of the spinach enrichments determined that pathogen risk groups 1 and 2 could be easily discriminated from the other groups, though some clustering of risk groups 1 and 2 was observed, likely representing their genomic similarity. Biomarker discovery identified metabolites that were significantly associated with risk groups and may be appropriate targets for potential biosensor development. This study has confirmed that metabolomics can be used to identify the presence of pathogenic E. coli likely to be implicated in human disease.

Quality of Dietary Supplements Containing Plant-Derived Ingredients Reconsidered by Microbiological Approach

Dietary supplements cover a wide range of products, the most popular are those containing plant-based ingredients. Supplements are consumed by consumers of all ages as well as by both healthy and sick people. The lack of unified regulation in this sector increases the probability that supplements are poor chemical and microbiological quality and can be dangerous for patients. The aim of this paper is to highlight selected issues associated with the microbiological quality of dietary supplements containing plant materials. We focus on the most recent reports referring to bacterial and fungal contaminations as well as the presence of mycotoxins. Dietary supplements containing plant ingredients commonly show a variety of microbial contaminants, which might be crucial for consumer safety. They often contain microorganisms potentially pathogenic to humans. Metabolites produced by microorganisms may pose a threat to the health of consumers. Because of that, in this review, we emphasize the risk that may be associated with the lack of appropriate studies of the quality of the supplements.

Microbial detection and identification methods: Bench top assays to omics approaches

Rapid detection of foodborne pathogens, spoilage microbes, and other biological contaminants in complex food matrices is essential to maintain food quality and ensure consumer safety. Traditional methods involve culturing microbes using a range of nonselective and selective enrichment methods, followed by biochemical confirmation among others. The time-to-detection is a key limitation when testing foods, particularly those with short shelf lives, such as fresh meat, fish, dairy products, and vegetables. Some recent detection methods developed include the use of spectroscopic techniques, such as matrix-assisted laser desorption ionization-time of flight along with hyperspectral imaging protocols.This review presents a comprehensive overview comparing insights into the principles, characteristics, and applications of newer and emerging techniques methods applied to the detection and identification of microbes in food matrices, to more traditional benchtop approaches. The content has been developed to provide specialist scientists a broad view of bacterial identification methods available in terms of their benefits and limitations, which may be useful in the development of future experimental design. The case is also made for incorporating some of these emerging methods into the mainstream, for example, underutilized potential of spectroscopic techniques and hyperspectral imaging.

Recent Advances in Necrotizing Enterocolitis Research: Strategies for Implementation in Clinical Practice

Necrotizing enterocolitis (NEC) is a complex inflammatory necrosis of the neonatal intestine, which is likely to require a multipronged approach for prevention and treatment. Despite identifying and defining NEC as a disease entity several decades back, no major progress has been made toward its early identification, treatment, or prevention. This article reviews the latest research strategies that are currently ongoing for early diagnosis and monitoring and prevention of the disease.

Translating 'big data': better understanding of host-pathogen interactions to control bacterial foodborne pathogens in poultry

Recent technological advances has led to the generation, storage, and sharing of colossal sets of information ('big data'), and the expansion of 'omics' in science. To date, genomics/metagenomics, transcriptomics, proteomics, and metabolomics are arguably the most ground breaking approaches in food and public safety. Here we review some of the recent studies of foodborne pathogens (Campylobacter spp., Salmonella spp., and Escherichia coli) in poultry using big data. Genomic/metagenomic approaches have reveal the importance of the gut microbiota in health and disease. They have also been used to identify, monitor, and understand the epidemiology of antibiotic-resistance mechanisms and provide concrete evidence about the role of poultry in human infections. Transcriptomics studies have increased our understanding of the pathophysiology and immunopathology of foodborne pathogens in poultry and have led to the identification of host-resistance mechanisms. Proteomic/metabolomic approaches have aided in identifying biomarkers and the rapid detection of low levels of foodborne pathogens. Overall, 'omics' approaches complement each other and may provide, at least in part, a solution to our current food-safety issues by facilitating the development of new rapid diagnostics, therapeutic drugs, and vaccines to control foodborne pathogens in poultry. However, at this time most 'omics' approaches still remain underutilized due to their high cost and the high level of technical skills required.

Current and Emerging Technologies for the Detection of Norovirus from Shellfish

Reports of norovirus infections associated with the consumption of contaminated bivalve molluscan shellfish negatively impact both consumers and commercial shellfish operators. Current virus recovery and PCR detection methods can be expensive and time consuming. Due to the lack of rapid, user-friendly and onsite/infield methods, it has been difficult to establish an effective virus monitoring regime that is able to identify contamination points across the production line (i.e., farm-to-plate) to ensure shellfish quality. The focus of this review is to evaluate current norovirus detection methods and discuss emerging approaches. Recent advances in omics-based detection approaches have the potential to identify novel biomarkers that can be incorporated into rapid detection kits for onsite use. Furthermore, some omics techniques have the potential to simultaneously detect multiple enteric viruses that cause human disease. Other emerging technologies discussed include microfluidic, aptamer and biosensor-based detection methods developed to detect norovirus with high sensitivity from a simple matrix. Many of these approaches have the potential to be developed as user-friendly onsite detection kits with minimal costs. However, more collaborative efforts on research and development will be required to commercialize such products. Once developed, these emerging technologies could provide a way forward that minimizes public health risks associated with shellfish consumption.

Non-destructive characterization of egg odor and fertilization status by SPME/GC-MS coupled with electronic nose

BACKGROUND

Early and non-destructive identification of fertile (F) eggs is a difficult task in the process of breeding laying hens. The odors emitted from unfertilized (UF), infertile (IF), and fertile (F) eggs were characterized by solid-phase microextraction / gas chromatograph-mass spectrometry (SPME/GC-MS) and electronic nose (E-nose) to determine their differences by principal component, partial least squares, and canonical discriminant analyses.

RESULTS

A total of 14 volatiles were identified in unhatched shell white Leghorn eggs, such as nonanal, decanal, 6-methyl-5-hepten-2-one, and 6,10-dimethyl-5,9-undecadien-2-one. Cedrene and decanal contributed greatly to the classification of UF and fertilized (Fd)/IF eggs; cedrene, decanal, 1-octanol and hexanal contributed greatly to the distinction between UF and IF eggs; heptanal might be the potential marker to determine F/IF eggs. P40/1, P10/2, P10/1, TA/2, T40/2 and T30/1, P30/1, P40/2, PA/2, T40/2 mostly contributed to the distinction between UF and Fd eggs and between F and IF eggs, respectively. Canonical discriminant analysis presented superior differentiating efficiency for almost all groups, and the odor differences between UF and Fd eggs were significantly larger than the differences between F and IF eggs.

CONCLUSION

Solid-phase microextraction / gas chromatograph-mass spectrometer combined with E-nose may have the potential to non-destructively distinguish UF, F, and IF eggs, which will provide a new perspective to understand the differences among them. © 2018 Society of Chemical Industry.

Identification of Putative Biomarkers Specific to Foodborne Pathogens Using Metabolomics

Metabolomics is one of the more recently developed "omics" that measures low molecular weight (typically < 1500 Da) compounds in biological samples. Metabolomics has been widely explored in environmental, clinical, and industrial biotechnology applications. However, its application to the area of food safety has been limited but preliminary work has demonstrated its value. This chapter describes an untargeted (nontargeted) metabolomics workflow using gas chromatography coupled to mass spectrometry (GC-MS) for characterizing three globally important foodborne pathogens, Escherichia coli O157:H7, Listeria monocytogenes, and Salmonella enterica, from selective enrichment liquid culture media. The workflow involves a detailed description of food spiking experiments followed by procedures for extraction of polar metabolites from media, analyzing the extracts using GC-MS and, finally, chemometric data analysis using the software "SIMCA" to identify potential pathogen-specific biomarkers.

Detection of Foodborne Pathogens Using Proteomics and Metabolomics-Based Approaches

Considering the short shelf-life of certain food products such as red meat, there is a need for rapid and cost-effective methods for pathogen detection. Routine pathogen testing in food laboratories mostly relies on conventional microbiological methods which involve the use of multiple selective culture media and long incubation periods, often taking up to 7 days for confirmed identifications. The current study investigated the application of omics-based approaches, proteomics using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-ToF MS) and metabolomics using gas chromatography-mass spectrometry (GC-MS), for detection of three red meat pathogens - Listeria monocytogenes, Salmonella enterica and Escherichia coli O157:H7. Species-level identification was achieved within 18 h for S. enterica and E. coli O157:H7 and 30 h for L. monocytogenes using MALDI-ToF MS analysis. For the metabolomics approach, metabolites were extracted directly from selective enrichment broth samples containing spiked meat samples (obviating the need for culturing on solid media) and data obtained using GC-MS were analyzed using chemometric methods. Putative biomarkers relating to L. monocytogenes, S. enterica and E. coli O157:H7 were observed within 24, 18, and 12 h, respectively, of inoculating meat samples. Many of the identified metabolites were sugars, fatty acids, amino acids, nucleosides and organic acids. Secondary metabolites such as cadaverine, hydroxymelatonin and 3,4-dihydroxymadelic acid were also observed. The results obtained in this study will assist in the future development of rapid diagnostic tests for these important foodborne pathogens.

Necrotizing enterocolitis: The intestinal microbiome, metabolome and inflammatory mediators

Necrotizing enterocolitis (NEC) is a disease of preterm infants and associated with significant mortality and morbidity. Although the pathogenesis of NEC is not clear, microbial dysbiosis, with a bloom of the phylum Proteobacteria, has been reported. Antibiotics and the use of H₂ blockers, which affect the gut microbiome, are associated with increased incidence of NEC. In association with dysbiosis, inflammatory processes are upregulated with increased Toll-like receptor signaling, leading to translocation of nuclear factor kappa-β, a transcription factor that induces transcription of various pro-inflammatory cytokines and chemokines. Microbial metabolites, short chain fatty acids including acetate and butyrate, may modulate immunity, inflammation, intestinal integrity and regulate transcription by epigenetic mechanisms. Evaluation of microbiome and metabolome may provide biomarkers for early diagnosis of NEC and microbial therapeutic approaches to correct microbial dysbiosis.

Targeted metabolic profiling rapidly differentiates Escherichia coli and Staphylococcus aureus at species and strain level

RATIONALE

Pathogenic foodborne bacteria have been associated with severe infectious disease in humans and animals worldwide. Rapid detection and screening of these foodborne pathogens are critical for our food safety. This study aimed at detecting Escherichia coli and Staphylococcus aureus, two important foodborne bacteria, at the species and strain/serovar level using a mass spectrometry (MS)-based targeted metabolic profiling approach.

METHODS

Ten E. coli strains (8 out of 10 were foodborne outbreak isolates) and four S. aureus strains were tested at two growth time points. A high-performance liquid chromatography/tandem mass spectrometry (HPLC/MS/MS)-based targeted metabolomics approach was applied for metabolic profile based bacteria detection. A total of 108 metabolites from multiple metabolic pathways were confidently detected from these bacteria.

RESULTS

Our study demonstrated that with only 4 h of enrichment in the same medium, the metabolic profiles from E. coli and S. aureus showed significant difference. Furthermore, seven out of ten E. coli strains and all four tested S. aureus strains showed strain/serovar-level differentiation at the 4-h time point, which indicated great potential for strain level stratification in future food screening using our MS-based targeted metabolic profiling approach.

CONCLUSIONS

A targeted metabolomics method was developed to demonstrate the utility of HPLC/MS/MS-based metabolic profiling in rapidly (4 h) differentiating E. coli and S. aureus bacteria, two of the most notorious foodborne bacteria, at both the species and strain/serovar levels. The results indicated that our approach has great potential in the future for fast and specific detection of foodborne pathogenic bacteria based on their metabolic diversity.

Applications of prebiotics in food industry: A review

Benefits of prebiotics for stimulating a healthy intestinal tract are well known. From suppression of pathogens to proliferation of indigenous bacteria of intestines, prebiotics have it all. Since the research on the scope of prebiotics is expanding, new applications are coming up every day thus upgrading the choices consumer has for a healthy living. Incorporation of prebiotics in a wide range of products that food industry offers on shelf is an innovative way to replace fat and sugars along with enhancing the mouthfeel by providing better tongue lubrication. In some cases, the thermal stability of the product is improved along with other sensory, textural and physiological benefits. This paper gives an overview of the various prebiotics available from different sources and their applications in various segments of food industry, notably dairy, beverage, processed fruit-vegetable, bakery, confectionary, extruded snack, sweetener, infant formula, pet food and livestock industry. The effects observed on addition of various prebiotics are also elaborated.

A plant pathogenic bacterium exploits the tricarboxylic acid cycle metabolic pathway of its insect vector

Huanglongbing in citrus is caused by a phloem-limited, uncultivable, gram-negative α-proteobacterium, Candidatus Liberibacter asiaticus (CLas). CLas is transmitted by the phloem-sucking insect, Diaphorina citri (Hemiptera: Liviidae), in a persistent, circulative, and propagative manner. In this study, we investigated the metabolomic and respiration rates changes in D. citri upon infection with CLas using gas chromatography-mass spectrometry (GC-MS) and gas exchange analysis. The level of glycine, _L-serine, _L-threonine, and gamma-amino butyric acid were higher in CLas-infected D. citri, while _L-proline, _L-aspartic acid, and _L-pyroglutamic acid were lower in CLas-infected D. citri compared with the control. Citric acid was increased in CLas-infected D. citri, whereas malic and succinic acids were reduced. Interestingly, most of the reduced metabolites such as malate, succinate, aspartate, and _L-proline are required for the growth of CLas. The increase in citric acid, serine, and glycine indicated that CLas induced glycolysis and the tricarboxylic acid cycle (TCA) in its vector. In agreement with the GC-MS results, the gene expression results also indicated that glycolysis and TCA were induced in CLas-infected D. citri and this was accompanied with an increases in respiration rate. Phosphoric acid and most of the sugar alcohols were higher in CLas-infected D. citri, indicating a response to the biotic stress or cell damage. Only slight increases in the levels of few sugars were observed in CLas-infected D. citri, which indicated that sugars are tightly regulated by D. citri. Our results indicated that CLas induces nutrient and energetic stress in its host insect. This study may provide some insights into the mechanism of colonization of CLas in its vector.

Livestock metabolomics and the livestock metabolome: A systematic review

Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular “omics” approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed.

Metabolic Phenotyping of Diet and Dietary Intake

Nutrition provides the building blocks for growth, repair, and maintenance of the body and is key to maintaining health. Exposure to fast foods, mass production of dietary components, and wider importation of goods have challenged the balance between diet and health in recent decades, and both scientists and clinicians struggle to characterize the relationship between this changing dietary landscape and human metabolism with its consequent impact on health. Metabolic phenotyping of foods, using high-density data-generating technologies to profile the biochemical composition of foods, meals, and human samples (pre- and postfood intake), can be used to map the complex interaction between the diet and human metabolism and also to assess food quality and safety. Here, we outline some of the techniques currently used for metabolic phenotyping and describe key applications in the food sciences, ending with a broad outlook at some of the newer technologies in the field with a view to exploring their potential to address some of the critical challenges in nutritional science.

Lambda Red-mediated Recombineering in the Attaching and Effacing Pathogen Escherichia albertii

Background

The ability to introduce site-specific mutations in bacterial pathogens is essential towards understanding their molecular mechanisms of pathogenicity. This has been greatly facilitated by the genetic engineering technique of recombineering. In recombineering, linear double- or single-stranded DNA molecules with two terminal homology arms are electroporated into hyperrecombinogenic bacteria that express a phage-encoded recombinase. The recombinase catalyzes the replacement of the endogenous allele with the exogenous allele to generate selectable or screenable recombinants. In particular, lambda red recombinase has been instrumental in engineering mutations to characterize the virulence arsenal of the attaching and effacing (A/E) pathogens enteropathogenic Escherichia coli (EPEC), enterohemorrhagic E. coli (EHEC), and Citrobacter rodentium. Escherichia albertii is another member of this taxon; however, the virulence of E. albertii remains cryptic despite accumulating evidence that E. albertii is an emerging pathogen. Multiple retrospective studies have reported that a substantial number of EPEC and EHEC isolates (~15 %) that were previously incriminated in human outbreaks actually belong to the E. albertii lineage. Thus, there is increased urgency to reliably identify and rapidly engineer mutations in E. albertii to systematically characterize its virulence determinants. To the best of our knowledge not a single chromosomal gene has been altered by targeted mutagenesis in E. albertii since it was first isolated almost 25 years ago. This is disconcerting because an E. albertii outbreak could cause significant morbidity and mortality owing to our inadequate understanding of its virulence program.

Results

In this report we describe a modified lambda red recombineering protocol to mutagenize E. albertii. As proof of principle, we successfully deleted three distinct virulence-associated genetic loci – ler, grlRA, and hfq – and replaced each wild type allele by a mutant allele with an encodable drug resistance cassette bracketed by FRT sites. Subsequently, the FRT-site flanked drug resistance marker was evicted by FLP-dependent site-specific recombination to generate excisants containing a solitary FRT site.

Conclusions

Our protocol will enable researchers to construct marked and unmarked genome-wide mutations in E. albertii, which, in turn, will illuminate its molecular mechanisms of pathogenicity and aid in developing appropriate preventative and therapeutic approaches to combat E. albertii outbreaks.

Food metabolomics: from farm to human

Metabolomics, one of the latest components in the suite of systems biology, has been used to understand the metabolism and physiology of living systems, including microorganisms, plants, animals and humans. Food metabolomics can be defined as the application of metabolomics in food systems, including food resources, food processing and diet for humans. The study of food metabolomics has increased gradually in the recent years, because food systems are directly related to nutrition and human health. This review describes the recent trends and applications of metabolomics to food systems, from farm to human, including food resource production, industrial food processing and food intake by humans.

Salmonella modulates metabolism during growth under conditions that induce expression of virulence genes

Salmonella enterica serovar Typhimurium (S. Typhimurium) is a facultative pathogen that uses complex mechanisms to invade and proliferate within mammalian host cells. To investigate possible contributions of metabolic processes to virulence in S. Typhimurium grown under conditions known to induce expression of virulence genes, we used a metabolomics-driven systems biology approach coupled with genome-scale modeling. First, we identified distinct metabolite profiles associated with bacteria grown in either rich or virulence-inducing media and report the most comprehensive coverage of the S. Typhimurium metabolome to date. Second, we applied an omics-informed genome-scale modeling analysis of the functional consequences of adaptive alterations in S. Typhimurium metabolism during growth under our conditions. Modeling efforts highlighted a decreased cellular capability to both produce and utilize intracellular amino acids during stationary phase culture in virulence conditions, despite significant abundance increases for these molecules as observed by our metabolomics measurements. Furthermore, analyses of omics data in the context of the metabolic model indicated rewiring of the metabolic network to support pathways associated with virulence. For example, cellular concentrations of polyamines were perturbed, as well as the predicted capacity for secretion and uptake.

Early microbial and metabolomic signatures predict later onset of necrotizing enterocolitis in preterm infants

BACKGROUND

Necrotizing enterocolitis (NEC) is a devastating intestinal disease that afflicts 10% of extremely preterm infants. The contribution of early intestinal colonization to NEC onset is not understood, and predictive biomarkers to guide prevention are lacking. We analyzed banked stool and urine samples collected prior to disease onset from infants <29 weeks gestational age, including 11 infants who developed NEC and 21 matched controls who survived free of NEC. Stool bacterial communities were profiled by 16S rRNA gene sequencing. Urinary metabolomic profiles were assessed by NMR.

RESULTS

During postnatal days 4 to 9, samples from infants who later developed NEC tended towards lower alpha diversity (Chao1 index, P = 0.086) and lacked Propionibacterium (P = 0.009) compared to controls. Furthermore, NEC was preceded by distinct forms of dysbiosis. During days 4 to 9, samples from four NEC cases were dominated by members of the Firmicutes (median relative abundance >99% versus <17% in the remaining NEC and controls, P < 0.001). During postnatal days 10 to 16, samples from the remaining NEC cases were dominated by Proteobacteria, specifically Enterobacteriaceae (median relative abundance >99% versus 38% in the other NEC cases and 84% in controls, P = 0.01). NEC preceded by Firmicutes dysbiosis occurred earlier (onset, days 7 to 21) than NEC preceded by Proteobacteria dysbiosis (onset, days 19 to 39). All NEC cases lacked Propionibacterium and were preceded by either Firmicutes (≥98% relative abundance, days 4 to 9) or Proteobacteria (≥90% relative abundance, days 10 to 16) dysbiosis, while only 25% of controls had this phenotype (predictive value 88%, P = 0.001). Analysis of days 4 to 9 urine samples found no metabolites associated with all NEC cases, but alanine was positively associated with NEC cases that were preceded by Firmicutes dysbiosis (P < 0.001) and histidine was inversely associated with NEC cases preceded by Proteobacteria dysbiosis (P = 0.013). A high urinary alanine:histidine ratio was associated with microbial characteristics (P < 0.001) and provided good prediction of overall NEC (predictive value 78%, P = 0.007).

CONCLUSIONS

Early dysbiosis is strongly involved in the pathobiology of NEC. These striking findings require validation in larger studies but indicate that early microbial and metabolomic signatures may provide highly predictive biomarkers of NEC.

Detection of Escherichia coli via VOC profiling using secondary electrospray ionization-mass spectrometry (SESI-MS)

Escherichia coli O157:H7 (EC O157:H7), as well as its recently emerging non-O157 relatives, are a notorious group of pathogenic bacteria associated with foodborne outbreaks. In this study, we demonstrated that secondary electrospray ionization mass spectrometry (SESI-MS) could be a rapid and accurate detection technology for foodborne pathogens. With SESI-MS volatile organic compound (VOC) profiling, we were able to detect and separate a group of eleven E. coli strains from two major foodborne bacteria, Staphylococcus aureus and Salmonella Typhimurium in three food modeling media. In addition, heatmap analysis of relative peak intensity show that there are six core peaks (m/z of 65, 91, 92, 117, 118 and 119) present and at a similar intensity in all eleven E. coli strains at the experimental conditions we tested. These peaks can be considered conserved VOC biomarkers for E. coli species (robustly produced after just 4 h of growth). Bacterial strain-level differentiation was also attempted via VOC profiling, and we found that EC O157:H7 and EC O145 were differentiable from all other EC strains under the conditions investigated.

GC-MS metabolomic differentiation of selected citrus varieties with different sensitivity to citrus huanglongbing

Huanglongbing (HLB) is the most destructive disease of citrus worldwide. The rapid identification of tolerant varieties is considered a critical step towards controlling HLB. GC-MS metabolite profiles were used to differentiate HLB-tolerant citrus varieties 'Poncirus trifoliata' (TR) and 'Carrizo citrange' (CAR) from HLB-sensitive varieties 'Madam Vinous sweet orange' (MV) and 'Duncan' grapefruit (DG). PCR analyses revealed that MV was the most sensitive variety followed by DG and the tolerant varieties CAR and TR. Metabolomic multivariate analysis allowed classification of the cultivars in apparent agreement with PCR results. Higher levels of the amino acids l-proline, l-serine, and l-aspartic acid, as well as the organic acids butanedioic and tetradecanoic acid, and accumulation of galactose in healthy plants were characteristic of the most sensitive variety MV when compared to all other varieties. Only galactose was significantly higher in DG when compared to the tolerant varieties TR and CAR. The tolerant varieties showed higher levels of l-glycine and mannose when compared to sensitive varieties MV and DG. Profiling of the sensitive varieties MV and DG over a 20-week period after inoculation of those with the HLB-containing material revealed strong responses of metabolites to HLB infection that differed from the response of the tolerant varieties. Significant changes of l-threonine level in the leaves from old mature flushes and l-serine, l-threonine, scyllo-inositol, hexadecanoic acid, and mannose in the leaves from young developing flushes were observed in MV. Significant changes in myo-inositol in old flushes and l-proline, indole, and xylose in new flushes were observed in DG.

Metabolomics in food science

Metabolomics, the newest member of the omics techniques, has become an important tool in agriculture, pharmacy, and environmental sciences. Advances in compound extraction, separation, detection, identification, and data analysis have allowed metabolomics applications in food sciences including food processing, quality, and safety. This chapter discusses recent advances and applications of metabolomics in food science.