Foodborne pathogens in the omics era

Vieira, Karolinny Cristiny de Oliveira; Silva, Hevelin Regiane Augusto da; Rocha, Isabela Poletto Masselli; Barboza, Emmanuel; Winkelströter, Lizziane Kretli

doi:10.1080/10408398.2021.1905603

Cited by 22 publications

(11 citation statements)

References 199 publications

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“…The release rate of the CNGA/C-AgNPs sample tended to be slow after 48 h, while the CNGA/m-C-AgNPs sample showed a long rapid release period of AgNPs, indicating that the immobilization effect of coaxial 3D printing remarkably controlled the release of AgNPs. Herein, common foodborne pathogenic bacteria [25], Escherichia coli and Staphylococcus aureus, were selected to evaluate the bacterial inhibition activity of CMC-based 3Dprinted cushioning-antibacterial packaging aerogel. In the presence of CNGA/C-AgNPs, the OD600 of bacterial suspension was significantly reduced compared with the control group, indicating that CNGA/C-AgNPs effectively inhibited the proliferation and activity of bacteria.…”

Section: Ag Release Behavior and Bacterial Inhibition Performance Of 3d-printed Cushioning-antibacterial Packaging Aerogelsmentioning

confidence: 99%

“…In the presence of CNGA/C-AgNPs, the OD600 of bacterial suspension was significantly reduced compared with the control group, indicating that CNGA/C-AgNPs effectively inhibited the proliferation and activity of bacteria. Compared with the control group, with the increase of time, the activity of Herein, common foodborne pathogenic bacteria [25], Escherichia coli and Staphylococcus aureus, were selected to evaluate the bacterial inhibition activity of CMC-based 3D-printed cushioning-antibacterial packaging aerogel. In the presence of CNGA/C-AgNPs, the OD 600 of bacterial suspension was significantly reduced compared with the control group, indicating that CNGA/C-AgNPs effectively inhibited the proliferation and activity of bacteria.…”

Section: Ag Release Behavior and Bacterial Inhibition Performance Of 3d-printed Cushioning-antibacterial Packaging Aerogelsmentioning

confidence: 99%

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3D-Printed Nanocellulose-Based Cushioning–Antibacterial Dual-Function Food Packaging Aerogel

et al. 2021

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Cushioning and antibacterial packaging are the requirements of the storage and transportation of fruits and vegetables, which are essential for reducing the irreversible quality loss during the process. Herein, the composite of carboxymethyl nanocellulose, glycerin, and acrylamide derivatives acted as the shell and chitosan/AgNPs were immobilized in the core by using coaxial 3D-printing technology. Thus, the 3D-printed cushioning–antibacterial dual-function packaging aerogel with a shell–core structure (CNGA/C–AgNPs) was obtained. The CNGA/C–AgNPs packaging aerogel had good cushioning and resilience performance, and the average compression resilience rate was more than 90%. Although AgNPs was slowly released, CNGA/C–AgNPs packaging aerogel had an obvious antibacterial effect on E. coli and S. aureus. Moreover, the CNGA/C–AgNPs packaging aerogel was biodegradable. Due to the customization capabilities of 3D-printing technology, the prepared packaging aerogel can be adapted to more application scenarios by accurately designing and regulating the microstructure of aerogels, which provides a new idea for the development of food intelligent packaging.

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Section: Ag Release Behavior and Bacterial Inhibition Performance Of 3d-printed Cushioning-antibacterial Packaging Aerogelsmentioning

confidence: 99%

Section: Ag Release Behavior and Bacterial Inhibition Performance Of 3d-printed Cushioning-antibacterial Packaging Aerogelsmentioning

confidence: 99%

3D-Printed Nanocellulose-Based Cushioning–Antibacterial Dual-Function Food Packaging Aerogel

et al. 2021

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“…Single-cell transcriptomics is the latest omics approach to unravel the dynamics of cellular reconstruction by measuring the concentration of mRNA to thousands of genes in each cell, which can be applied in the study of gastrointestinal pathogens [ 150 ]. Transcriptomics analysis using Serial Analysis and Cap Analysis of Gene Expression (SAGE/CAGE), and microarrays also have been used to identify the present of nadA in detection of Salmonella enterica [ 151 , 152 , 153 ] and EHEC EDL933 in detection of Escherichia coli [ 154 ].…”

Section: Omics-based Technologies For Age Diagnosis and Managementmentioning

confidence: 99%

“…As such, metabolomics analysis can be used to detect Salmonella enterica serovar Typhimurium. The most widely used techniques in metabolomics analysis are gas chromatography-mass spectrometry (GC-MS), liquid chromatography–mass spectrometry (LC-MS), and capillary electrophoresis coupled to mass spectrometry (CE-MS) [ 154 , 160 , 161 ]. Liquid chromatography–mass spectrometry (LC-MS) is also the metabolomic analysis technique used to detect changes in gut microbiota in children with diarrhoea caused by diarrhoeagenic Escherichia coli (DEC), as DEC-infected children and healthy children have a statistically different composition of microbiota [ 162 ].…”

Section: Omics-based Technologies For Age Diagnosis and Managementmentioning

confidence: 99%

Acute Infectious Gastroenteritis: The Causative Agents, Omics-Based Detection of Antigens and Novel Biomarkers

et al. 2021

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Acute infectious gastroenteritis (AGE) is among the leading causes of mortality in children less than 5 years of age worldwide. There are many causative agents that lead to this infection, with rotavirus being the commonest pathogen in the past decade. However, this trend is now being progressively replaced by another agent, which is the norovirus. Apart from the viruses, bacteria such as Salmonella and Escherichia coli and parasites such as Entamoeba histolytica also contribute to AGE. These agents can be recognised by their respective biological markers, which are mainly the specific antigens or genes to determine the causative pathogen. In conjunction to that, omics technologies are currently providing crucial insights into the diagnosis of acute infectious gastroenteritis at the molecular level. Recent advancement in omics technologies could be an important tool to further elucidate the potential causative agents for AGE. This review will explore the current available biomarkers and antigens available for the diagnosis and management of the different causative agents of AGE. Despite the high-priced multi-omics approaches, the idea for utilization of these technologies is to allow more robust discovery of novel antigens and biomarkers related to management AGE, which eventually can be developed using easier and cheaper detection methods for future clinical setting. Thus, prediction of prognosis, virulence and drug susceptibility for active infections can be obtained. Case management, risk prediction for hospital-acquired infections, outbreak detection, and antimicrobial accountability are aimed for further improvement by integrating these capabilities into a new clinical workflow.

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“…Foodborne pathogens include specific bacterial species consisting of spore‐forming and nonspore‐forming strains, which can either produce preformed toxins in the food or inside the human body (intestine) and lead to several types of mild to severe symptoms in consumers. Some examples are Clostridium perfringens , Campylobacter spp., Listeria monocytogenes , Vibrio parahaemolyticus , Bacillus cereus , and Escherichia coli (Banerji et al., 2021; Vieira et al., 2021). Bacterial contaminants associated with food spoilage and foodborne outbreaks have been investigated and reported (Table 1).…”

Section: Introductionmentioning

confidence: 99%

Hyperspectral imaging and machine learning in food microbiology: Developments and challenges in detection of bacterial, fungal, and viral contaminants

Soni

Dixit

Reis

et al. 2022

Comp Rev Food Sci Food Safe

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Hyperspectral imaging (HSI) is a robust and nondestructive method that can detect foreign particles such as microbial, chemical, and physical contamination in food. This review summarizes the work done in the last two decades in this field with a highlight on challenges, risks, and research gaps. Considering the challenges of using HSI on complex matrices like food (e.g., the confounding and masking effects of background signals), application of machine learning and modeling approaches that have been successful in achieving better accuracy as well as increasing the detection limit have also been discussed here. Foodborne microbial contaminants such as bacteria, fungi, viruses, yeast, and protozoa are of interest and concern to food manufacturers due to the potential risk of either food poisoning or food spoilage. Detection of these contaminants using fast and efficient methods would not only prevent outbreaks and recalls but will also increase consumer acceptance and demand for shelf-stable food products. The conventional culture-based methods for microbial detection are time and labor-intensive, whereas hyperspectral imaging (HSI) is robust, nondestructive with minimum sample preparation, and has gained significant attention due to its rapid approach to detection of microbial contaminants. This review is a comprehensive summary of the detection of bacterial, viral, and fungal contaminants in food with detailed emphasis on the specific modeling and datamining approaches used to overcome the specific challenges associated with background and data complexity.

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Foodborne pathogens in the omics era

Cited by 22 publications

References 199 publications

3D-Printed Nanocellulose-Based Cushioning–Antibacterial Dual-Function Food Packaging Aerogel

3D-Printed Nanocellulose-Based Cushioning–Antibacterial Dual-Function Food Packaging Aerogel

Acute Infectious Gastroenteritis: The Causative Agents, Omics-Based Detection of Antigens and Novel Biomarkers

Hyperspectral imaging and machine learning in food microbiology: Developments and challenges in detection of bacterial, fungal, and viral contaminants

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