scholarly journals Sampling and Homogenization Strategies Significantly Influence the Detection of Foodborne Pathogens in Meat

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Alexander Rohde ◽  
Jens Andre Hammerl ◽  
Bernd Appel ◽  
Ralf Dieckmann ◽  
Sascha Al Dahouk
Keyword(s):  
Foodborne Pathogens ◽  
Sample Pretreatment ◽  
Food Samples ◽  
Surface Contamination ◽  
Food Microbiology ◽  
Good Recovery ◽  
Homogenization Procedure ◽  
The Core ◽  
Microbiological Testing ◽  
Entire Matrix

Efficient preparation of food samples, comprising sampling and homogenization, for microbiological testing is an essential, yet largely neglected, component of foodstuff control.Salmonella entericaspiked chicken breasts were used as a surface contamination model whereas salami and meat paste acted as models of inner-matrix contamination. A systematic comparison of different homogenization approaches, namely, stomaching, sonication, and milling by FastPrep-24 or SpeedMill, revealed that for surface contamination a broad range of sample pretreatment steps is applicable and loss of culturability due to the homogenization procedure is marginal. In contrast, for inner-matrix contamination long treatments up to 8 min are required and only FastPrep-24 as a large-volume milling device produced consistently good recovery rates. In addition, sampling of different regions of the spiked sausages showed that pathogens are not necessarily homogenously distributed throughout the entire matrix. Instead, in meat paste the core region contained considerably more pathogens compared to the rim, whereas in the salamis the distribution was more even with an increased concentration within the intermediate region of the sausages. Our results indicate that sampling and homogenization as integral parts of food microbiology and monitoring deserve more attention to further improve food safety.

scholarly journals Foodborne Toxigenic Agents Investigated in Central Italy: An Overview of a Three-Year Experience (2018–2020)

Toxins ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 40
Author(s):  
Valeria Russini ◽  
Carlo Corradini ◽  
Maria Laura De Marchis ◽  
Tatiana Bogdanova ◽  
Sarah Lovari ◽  
...  
Keyword(s):  
Foodborne Pathogens ◽  
Central Italy ◽  
Bacterial Pathogen ◽  
Food Samples ◽  
Food Microbiology ◽  
Clinical Samples ◽  
Public Health Issue ◽  
Fully Integrated ◽  
Source Of Infection ◽  
Clinical Diagnoses

Foodborne diseases (FBDs) represent a worldwide public health issue, given their spreadability and the difficulty of tracing the sources of contamination. This report summarises the incidence of foodborne pathogens and toxins found in food, environmental and clinical samples collected in relation to diagnosed or suspected FBD cases and submitted between 2018 and 2020 to the Food Microbiology Unit of the Istituto Zooprofilattico Sperimentale del Lazio e della Toscana (IZSLT). Data collected from 70 FBD investigations were analysed: 24.3% of them started with an FBD diagnosis, whereas a further 41.4% involved clinical diagnoses based on general symptomatology. In total, 5.6% of the 340 food samples analysed were positive for the presence of a bacterial pathogen, its toxins or both. Among the positive samples, more than half involved meat-derived products. Our data reveal the probable impact of the COVID-19 pandemic on the number of FBD investigations conducted. In spite of the serious impact of FBDs on human health and the economy, the investigation of many foodborne outbreaks fails to identify the source of infection. This indicates a need for the competent authorities to continue to develop and implement a more fully integrated health network.

Sequence of Colonization Determines the Composition of Mixed Biofilms by Escherichia coli O157:H7 and O111:H8 Strains†

2015 ◽  
Vol 78 (8) ◽  
pp. 1554-1559 ◽  
Author(s):  
RONG WANG ◽  
NORASAK KALCHAYANAND ◽  
JAMES L. BONO
Keyword(s):  
Escherichia Coli ◽  
Foodborne Pathogens ◽  
Early Stage ◽  
Critical Role ◽  
The United States ◽  
Food Samples ◽  
E Coli ◽  
Cell Percentage ◽  
Composition And Structure ◽  
Biofilm Development

Bacterial biofilms are one of the potential sources of cross-contamination in food processing environments. Shiga toxin–producing Escherichia coli (STEC) O157:H7 and O111:H8 are important foodborne pathogens capable of forming biofilms, and the coexistence of these two STEC serotypes has been detected in various food samples and in multiple commercial meat plants throughout the United States. Here, we investigated how the coexistence of these two STEC serotypes and their sequence of colonization could affect bacterial growth competition and mixed biofilm development. Our data showed that E. coli O157:H7 strains were able to maintain a higher cell percentage in mixed biofilms with the co-inoculated O111:H8 companion strains, even though the results of planktonic growth competition were strain dependent. On solid surfaces with preexisting biofilms, the sequence of colonization played a critical role in determining the composition of the mixed biofilms because early stage precolonization significantly affected the competition results between the E. coli O157:H7 and O111:H8 strains. The precolonizer of either serotype was able to outgrow the other serotype in both planktonic and biofilm phases. The competitive interactions among the various STEC serotypes would determine the composition and structure of the mixed biofilms as well as their potential risks to food safety and public health, which is largely influenced by the dominant strains in the mixtures. Thus, the analysis of mixed biofilms under various conditions would be of importance to determine the nature of mixed biofilms composed of multiple microorganisms and to help implement the most effective disinfection operations accordingly.

An Outbreak of Salmonella Chester Infection in Canada: Rare Serotype, Uncommon Exposure, and Unusual Population Demographic Facilitate Rapid Identification of Food Vehicle

2012 ◽  
Vol 75 (4) ◽  
pp. 738-742 ◽  
Author(s):  
JOHN TAYLOR ◽  
ELENI GALANIS ◽  
LYNN WILCOTT ◽  
LINDA HOANG ◽  
JASON STONE ◽  
...  
Keyword(s):  
Rapid Identification ◽  
Food Samples ◽  
Grocery Store ◽  
Control Measures ◽  
Source Control ◽  
Public Health Agencies ◽  
Patient Interviews ◽  
Microbiological Testing ◽  
Canadian Provinces ◽  
Population Demographic

Salmonella Chester infection has rarely been reported in the literature. In 2010, 33 case patients were reported in 2 months in four Canadian provinces. We conducted an outbreak investigation in collaboration with public health agencies, food safety specialists, regulatory agencies, grocery store chains, and the product distributor. We used case patient interviews, customer loyalty cards, and microbiological testing of clinical and food samples to identify nationally distributed head cheese as the food vehicle responsible for the outbreak. The rare serotype, a limited affected demographic group, and an uncommon exposure led to the rapid identification of the source. Control measures were implemented within 9 days of notification of the outbreak.

Comparison of Three-Class Attributes Sampling Plans and Variables Sampling Plans for Lot Acceptance Sampling in Food Microbiology

1986 ◽  
Vol 49 (9) ◽  
pp. 724-728 ◽  
Author(s):  
GEORGE A. JARVIS ◽  
STEPHEN A. MALCOLM
Keyword(s):  
Statistical Tests ◽  
Microbiological Quality ◽  
Food Microbiology ◽  
Acceptance Sampling ◽  
Sampling Plans ◽  
Discriminatory Ability ◽  
Increased Risk ◽  
Acceptance Sampling Plans ◽  
Microbiological Testing ◽  
Correct Application

Lot acceptance sampling is an established method of assessing the microbiological quality and safety of batches or consignments of food, but the choice between three-class attributes plans and variables plans is not always clear. Application of variables plans requires that the microorganism of concern be distributed normally, or log-normally. When such is not true, variables plans may place either the consumer or the producer at increased risk. Validation of normality is therefore essential when using variables plans. However, with small numbers of sample units as are typically analyzed in microbiological testing of food, statistical tests are unlikely to detect non-normality. Three-class attributes plans do not require strong distributional assumptions for correct application, and as well they have several practical and operational advantages over variables plans. Moreover, three-class attributes plans assess lot quality in a fashion fundamentally different from variables plans, and this difference precludes the usual statistical comparisons based on relative discriminatory ability. We conclude that when selecting acceptance sampling plans for microbiological testing of food, whether the plans be for regulatory, port-of-entry or in-plant purposes, three-class plans are generally preferable to variables plans.

scholarly journals Preparation of Fluorescent Molecularly Imprinted Polymers via Pickering Emulsion Interfaces and the Application for Visual Sensing Analysis of Listeria Monocytogenes

Polymers ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 984 ◽  
Author(s):  
Xiaolei Zhao ◽  
Yan Cui ◽  
Junping Wang ◽  
Junying Wang
Keyword(s):  
Listeria Monocytogenes ◽  
Sample Pretreatment ◽  
Spherical Shape ◽  
Pickering Emulsion ◽  
Food Samples ◽  
Water Soluble ◽  
Water Emulsion ◽  
Molecularly Imprinted ◽  
Oil In Water ◽  
Oil In Water Emulsion

In this work, a novel molecularly imprinted polymer (MIP) with water-soluble CdTe quantum dots (QDs) was synthesized by oil-in-water Pickering emulsion polymerization using whole Listeria monocytogenes as the template. Listeria monocytogenes was first treated by acryloyl-functionalized chitosan with QDs to form a bacteria–chitosan network as the water phase. This was then stabilized in an oil-in-water emulsion comprising a cross-linker, monomer, and initiator, causing recognition sites on the surface of microspheres embedded with CdTe QDs. The resulting MIP microspheres enabled selective capture of the target bacteria via recognition cavities. The target bacteria Listeria monocytogenes was detected. Scanning electron microscopy (SEM) characterization showed that the MIPs had a rough spherical shape. There was visual fluorescence detection via quenching in the presence of the target molecule, which offered qualitative detection of Listeria monocytogenes in milk and pork samples. The developed method simplified the analysis process and did not require any sample pretreatment. In addition, the fluorescence sensor provided an effective, fast, and convenient method for Listeria monocytogenes detection in food samples.

Isolation and Characterization of Non-O157 Shiga Toxin–Producing Escherichia coli in Foods Sold at Retail Markets in China

2019 ◽  
Vol 83 (3) ◽  
pp. 460-466
Author(s):  
GUANGZHU YANG ◽  
SHUHONG ZHANG ◽  
YUANBIN HUANG ◽  
QINGHUA YE ◽  
JUMEI ZHANG ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Foodborne Pathogens ◽  
Shiga Toxin ◽  
Multidrug Resistant ◽  
Food Samples ◽  
High Genetic Diversity ◽  
Retail Markets ◽  
Republic Of China ◽  
Isolation And Characterization ◽  
High Prevalence

ABSTRACT Non-O157 Shiga toxin–producing Escherichia coli (STEC) strains are significant foodborne pathogens that can cause acute diarrhea in humans. This study was conducted to investigate the contamination by non-O157 STEC in different types of food sold at retail markets in the People's Republic of China and to characterize non-O157 STEC strains. From May 2012 to April 2014, 1,200 retail food samples were collected from markets in 24 cities in China. Forty-four non-O157 isolates were recovered from 43 STEC-positive samples. Of the isolates, 22 and 19 carried the stx1 and stx2 genes, respectively, and 3 harbored both stx1 and stx2. stx1a and stx2a were the most prevalent stx subtypes. Other virulence genes, ent, hlyA, astA, eae, espB, iha, subAB, and tia, were commonly detected. Diverse O serogroups were identified among these isolates. Multilocus sequence typing indicated the high genetic diversity of the isolates. Thirty-two sequence types (STs) were identified among the 44 isolates, with ST383 (9.09%), ST134 (6.82%), and ST91 (6.82%) the most prevalent. Nine new STs were found. The isolates had a high prevalence of resistance to cephalothin, ampicillin, tetracycline, trimethoprim-sulfamethoxazole, nalidixic acid, streptomycin, and chloramphenicol. Twenty isolates (45.45%) were resistant to at least three antibiotics. This study provides updated surveillance data for non-O157 STEC isolates from foods sold at retail markets. Virulent and multidrug-resistant non-O57 STEC strains were isolated from all types of food. Our findings highlight the need for increased monitoring of non-O157 STEC in retail foods. HIGHLIGHTS

Microbiological Quality and Safety of Ready-to-Eat Street-Vended Foods in Johannesburg, South Africa

1999 ◽  
Vol 62 (11) ◽  
pp. 1278-1284 ◽  
Author(s):  
FRANCINA M. MOSUPYE ◽  
ALEXANDER von HOLY
Keyword(s):  
South Africa ◽  
Foodborne Pathogens ◽  
Water Samples ◽  
Microbiological Quality ◽  
Food Samples ◽  
Quality And Safety ◽  
Salmonella Spp ◽  
E Coli ◽  
Bacillus Spp ◽  
Staphylococcus Spp

Fifty-one ready-to-eat street foods, 18 dishwater, and 18 surface swab samples were collected from six vendors in Johannesburg, South Africa. Food temperatures were recorded at the time of sampling. Standard methods were used to determine aerobic plate counts (APCs), spore counts (SCs), and Enterobacteriaceae counts (ECs) for food samples as well as coliform counts (CCs) for water and swab samples. In addition, Petrifilm Escherichia coli count (PC) plates were used for the enumeration of coliforms in food, water, and swab samples. The presence of selected foodborne pathogens in the food samples as well as the presence of nonpathogenic E. coli 1 (in food and water samples) was also tested for. Predominant colonies isolated from APC plates were characterized to the genus level. Holding temperatures for cooked meats and gravies ranged from 42.0 to 94.0°C, and those for uncooked salads ranged from 29.0 to 39.0°C. Mean APC values of 3.4 (±0.4) log CFU/g, 4.0 (±1.2) log CFU/ml, and 2.1 (±0.4) log CFU/25 cm2 were obtained for food, water, and swab samples, respectively. Mean SC values of 1.6 (±0.2) log CFU/g and 1.5 (±0.3) log CFU/25 cm2 were obtained for food and swab samples, respectively. A mean EC value of 2.0 (±0.4) log CFU/g for food samples and mean CC values of 2.5 (±0.3) log CFU/ml and 1.3 (±0.3) log CFU/25 cm2 for water and swab samples, respectively, were determined. Mean PC values of 1.6 (±0.1) log CFU/g, 1.9 (±0.6) log CFU/ml, and 1.4 (±0.4) log CFU/25 cm2 were determined for food, water, and swab samples, respectively. Bacillus cereus was detected in 22%, Clostridium perfringens in 16%, Salmonella spp. in 2%, and E. coli (non-O157:H+) in 2% of the 51 food samples. E. coli was found in 14 water samples (78%) and in 3 food samples (6%). Campylobacter spp., Listeria monocytogenes, Staphylococcus aureus, Vibrio cholerae, and Yersinia enterocolitica were also tested for in the food samples, but they were not detected. The 340 isolates obtained from APC plates for food, water, and swab samples were predominantly Bacillus spp., Micrococcus spp., and Staphylococcus spp. for all three sample types. It was concluded that the foods analyzed in this study were of acceptable quality and safety.

scholarly journals Microbiomes of commercially-available pine nuts and sesame seeds

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252605
Author(s):  
Megan Fay ◽  
Joelle K. Salazar ◽  
Padmini Ramachandran ◽  
Diana Stewart
Keyword(s):  
Foodborne Pathogens ◽  
Seed Type ◽  
Sequencing Technology ◽  
Community Members ◽  
Core Microbiome ◽  
Sesame Seeds ◽  
The Core ◽  
Pine Nut ◽  
The Family ◽  
Rrna Sequencing

Metagenomic analysis of food is becoming more routine and can provide important information pertaining to the shelf life potential and the safety of these products. However, less information is available on the microbiomes associated with low water activity foods. Pine nuts and sesame seeds, and food products which contain these ingredients, have been associated with recalls due to contamination with bacterial foodborne pathogens. The objective of this study was to identify the microbial community of pine nuts and sesame seeds using targeted 16S rRNA sequencing technology. Ten different brands of each seed type were assessed, and core microbiomes were determined. A total of 21 and 16 unique taxa with proportional abundances >1% in at least one brand were identified in the pine nuts and sesame seeds, respectively. Members of the core pine nut microbiome included the genera Alishewanella, Aminivibrio, Mycoplasma, Streptococcus, and unassigned OTUs in the families of Desulfobacteraceae and Xanthomonadaceae. For sesame seeds, the core microbiome included Aminivibrio, Chryseolina, Okibacterium, and unassigned OTUs in the family Flavobacteriaceae. The microbiomes of these seeds revealed that these products are dominated by environmental bacterial genera commonly isolated from soil, water, and plants; bacterial genera containing species known as commensal organisms were also identified. Understanding these microbiomes can aid in the risk assessment of these products by identifying food spoilage potential and community members which may co-enrich with foodborne bacterial pathogens.

scholarly journals Snipe: highly sensitive pathogen detection from metagenomic sequencing data

2021 ◽  
Author(s):  
Lihong Huang ◽  
Bin Hong ◽  
Wenxian Yang ◽  
Liansheng Wang ◽  
Rongshan Yu
Keyword(s):  
Foodborne Pathogens ◽  
Pathogen Detection ◽  
High Sensitivity ◽  
High Specificity ◽  
Correction Method ◽  
Food Samples ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Metagenomics Data ◽  
Species Specific

Abstract Metagenomics data provide rich information for the detection of foodborne pathogens from food and environmental samples that are mixed with complex background bacteria strains. While pathogen detection from metagenomic sequencing data has become an activity of increasing interest, shotgun sequencing of uncultured food samples typically produces data that contain reads from many different organisms, making accurate strain typing a challenging task. Particularly, as many pathogens may contain a common set of genes that are highly similar to those from normal bacteria in food samples, traditional strain-level abundance profiling approaches do not perform well at detecting pathogens of very low abundance levels. To overcome this limitation, we propose an abundance correction method based on species-specific genomic regions to achieve high sensitivity and high specificity in target pathogen detection at low abundance.

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