scholarly journals Microbial Profiles of Retail Pacific Oysters (Crassostrea gigas) From Guangdong Province, China

2021 ◽  
Vol 12 ◽  
Author(s):  
Mingjia Yu ◽  
Xiaobo Wang ◽  
Aixian Yan
Keyword(s):  
Microbial Communities ◽  
Crassostrea Gigas ◽  
Pathogenic Bacteria ◽  
High Throughput Sequencing ◽  
Vibrio Vulnificus ◽  
Foodborne Pathogen ◽  
Guangdong Province ◽  
Sequencing Analysis ◽  
Alpha And Beta Diversity ◽  
Pacific Oysters

Oysters are one of the main aquatic products sold in coastal areas worldwide and are popular among consumers because of their delicious taste and nutritional value. However, the microorganisms present in oysters may pose health risks to consumers. In this study, the microbial communities of Pacific oysters (Crassostrea gigas) collected from aquatic product markets in three cities (Guangzhou, Zhuhai, and Jiangmen) of Guangdong Province, China, where raw oysters are popular, were investigated. The plate counts of viable bacteria in oysters collected in the three cities were all approximately 2 log colony-forming units/g. High-throughput sequencing analysis of the V3–V4 region of the 16Sribosomal DNA gene showed a high level of microbial diversity in oysters, as evidenced by both alpha and beta diversity analysis. Proteobacteria, Bacteroidetes, and Firmicutes were the dominant phyla of the microorganisms present in these samples. A variety of pathogenic bacteria, including the fatal foodborne pathogen Vibrio vulnificus, were found, and Vibrio was the dominant genus. Additionally, the relationship between other microbial species and pathogenic microorganisms may be mostly symbiotic in oysters. These data provide insights into the microbial communities of retail oysters in the Guangdong region and indicate a considerable risk related to the consumption of raw oysters.

Effects of Flash Freezing, Followed by Frozen Storage, on Reducing Vibrio parahaemolyticus in Pacific Raw Oysters (Crassostrea gigas)

2009 ◽  
Vol 72 (1) ◽  
pp. 174-177 ◽  
Author(s):  
CHENGCHU LIU ◽  
JIANZHANG LU ◽  
YI-CHENG SU
Keyword(s):  
Crassostrea Gigas ◽  
Vibrio Parahaemolyticus ◽  
Vibrio Vulnificus ◽  
Frozen Storage ◽  
Most Probable Number ◽  
Freezing Process ◽  
Probable Number ◽  
Pacific Oysters ◽  
Subsequent Storage ◽  
Shellfish Sanitation

This study investigated the effects of flash freezing, followed by frozen storage, on reducing Vibrio parahaemolyticus in Pacific raw oysters. Raw Pacific oysters were inoculated with a five-strain cocktail of V. parahaemolyticus at a total level of approximately 3.5 × 105 most probable number (MPN) per gram. Inoculated oysters were subjected to an ultralow flash-freezing process (−95.5°C for 12 min) and stored at −10, −20, and −30°C for 6 months. Populations of V. parahaemolyticus in the oysters declined slightly by 0.22 log MPN/g after the freezing process. Subsequent storage of frozen oysters at −10, −20, and −30°C resulted in considerable reductions of V. parahaemolyticus in the oysters. Storing oysters at −10°C was more effective in inactivating V. parahaemolyticus than was storage at −20 or −30°C. Populations of V. parahaemolyticus in the oysters declined by 2.45, 1.71, and 1.45 log MPN/g after 1 month of storage at −10, −20, and −30°C, respectively, and continued to decline during the storage. The levels of V. parahaemolyticus in oysters were reduced by 4.55, 4.13, and 2.53 log MPN/g after 6 months of storage at −10, −20, and −30°C, respectively. Three process validations, each separated by 1 week and conducted according to the National Shellfish Sanitation Program's postharvest processing validation–verification interim guidance for Vibrio vulnificus and Vibrio parahaemolyticus, confirmed that a process of flash freezing, followed by storage at −21 ± 2°C for 5 months, was capable of achieving greater than 3.52-log (MPN/g) reductions of V. parahaemolyticus in half-shell Pacific oysters.

scholarly journals Primary Processing and Storage Affect the Dominant Microbiota of Fresh and Chill-Stored Sea Bass Products

Foods ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 671
Author(s):  
Faidra Syropoulou ◽  
Foteini F. Parlapani ◽  
Stefanos Kakasis ◽  
George-John E. Nychas ◽  
Ioannis S. Boziaris
Keyword(s):  
Shelf Life ◽  
Microbial Communities ◽  
Pathogenic Bacteria ◽  
Sea Bass ◽  
Rrna Gene ◽  
Sequencing Analysis ◽  
Primary Processing ◽  
Shewanella Species ◽  
Processing And Storage ◽  
And Storage

The cultivable microbiota isolated from three sea bass products (whole, gutted, and filleted fish from the same batch) during chilled storage and the effect of primary processing on microbial communities in gutted and filleted fish were studied. Microbiological and sensory changes were also monitored. A total of 200 colonies were collected from TSA plates at the beginning and the end of fish shelf-life, differentiated by High Resolution Sequencing (HRM) and identified by sequencing analysis of the V3–V4 region of the 16S rRNA gene. Pseudomonas spp. followed by potential pathogenic bacteria were initially found, while Pseudomonasgessardii followed by other Pseudomonas or Shewanella species dominated at the end of fish shelf-life. P. gessardii was the most dominant phylotype in the whole sea bass, P. gessardii and S. baltica in gutted fish, while P. gessardii and P. fluorescens were the most dominant bacteria in sea bass fillets. To conclude, primary processing and storage affect microbial communities of gutted and filleted fish compared to the whole fish. HRM analysis can easily differentiate bacteria isolated from fish products and reveal the contamination due to handling and/or processing, and so help stakeholders to immediately tackle problems related with microbial quality or safety of fish.

scholarly journals Profiling Bacterial Diversity and Potential Pathogens in Wastewater Treatment Plants Using High-Throughput Sequencing Analysis

2019 ◽  
Vol 7 (11) ◽  
pp. 506 ◽  
Author(s):  
Cecilia Oluseyi Osunmakinde ◽  
Ramganesh Selvarajan ◽  
Bhekie B. Mamba ◽  
Titus A.M. Msagati
Keyword(s):  
Wastewater Treatment ◽  
Pathogenic Bacteria ◽  
High Throughput Sequencing ◽  
Wastewater Treatment Plants ◽  
Bacterial Pathogens ◽  
Size Analysis ◽  
Sequencing Analysis ◽  
Linear Discriminant ◽  
Treated Effluent ◽  
Wastewater Treatment Systems

Next-generation sequencing provides new insights into the diversity and structure of bacterial communities, as well as the fate of pathogens in wastewater treatment systems. In this study, the bacterial community structure and the presence of pathogenic bacteria in three wastewater treatment plants across Gauteng province in South Africa were studied. The physicochemical results indicated that the quality of wastewater varies considerably from one plant to the others. Proteobacteria, Actinobacteria, Firmicutes, and Chloroflexi were the dominant phyla across the three wastewater treatment plants, while Alphaproteobacteria, Actinobacteria, Bacilli, and Clostridia were the dominant classes. The dominant bacterial functions were highly associated with carbohydrate, energy, and amino acid metabolism. In addition, potential pathogenic bacterial members identified from the influent/effluent samples included Roseomonas, Bacillus, Pseudomonas, Clostridium, Mycobacterium, Methylobacterium, and Aeromonas. The results of linear discriminant analysis (LDA) effect size analysis also confirmed that these bacterial pathogens were significantly abundant in the wastewater treatment systems. Further, the results of this study highlighted that the presence of bacterial pathogens in treated effluent pose a potential contamination risk, transmitted through soil, agriculture, water, or sediments. There is thus a need for continuous monitoring of potential pathogens in wastewater treatment plants (WWTPs) in order to minimize public health risk.

A New Approach for Predicting the Value of Gene Expression: Two-way Collaborative Filtering

2019 ◽  
Vol 14 (6) ◽  
pp. 480-490 ◽  
Author(s):  
Tuncay Bayrak ◽  
Hasan Oğul
Keyword(s):  
Gene Expression ◽  
Regression Model ◽  
Collaborative Filtering ◽  
High Throughput Sequencing ◽  
Mean Squared Error ◽  
Experimental Studies ◽  
Kernel Functions ◽  
Feature Representation ◽  
Sequencing Analysis ◽  
Computational Systems Biology

Background: Predicting the value of gene expression in a given condition is a challenging topic in computational systems biology. Only a limited number of studies in this area have provided solutions to predict the expression in a particular pattern, whether or not it can be done effectively. However, the value of expression for the measurement is usually needed for further meta-data analysis. Methods: Because the problem is considered as a regression task where a feature representation of the gene under consideration is fed into a trained model to predict a continuous variable that refers to its exact expression level, we introduced a novel feature representation scheme to support work on such a task based on two-way collaborative filtering. At this point, our main argument is that the expressions of other genes in the current condition are as important as the expression of the current gene in other conditions. For regression analysis, linear regression and a recently popularized method, called Relevance Vector Machine (RVM), are used. Pearson and Spearman correlation coefficients and Root Mean Squared Error are used for evaluation. The effects of regression model type, RVM kernel functions, and parameters have been analysed in our study in a gene expression profiling data comprising a set of prostate cancer samples. Results: According to the findings of this study, in addition to promising results from the experimental studies, integrating data from another disease type, such as colon cancer in our case, can significantly improve the prediction performance of the regression model. Conclusion: The results also showed that the performed new feature representation approach and RVM regression model are promising for many machine learning problems in microarray and high throughput sequencing analysis.

scholarly journals Seasonal Variation Characteristics of Bacteria and Fungi in PM2.5 in Typical Basin Cities of Xi’an and Linfen, China

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 809
Author(s):  
Sen Wang ◽  
Wanyu Liu ◽  
Jun Li ◽  
Haotian Sun ◽  
Yali Qian ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Relative Abundance ◽  
Pathogenic Bacteria ◽  
High Throughput Sequencing ◽  
Fine Particulate Matter ◽  
Ecological Functions ◽  
Factors Affecting ◽  
Bacterial Phyla ◽  
Variation Characteristics ◽  
Bacteria And Fungi

Microorganisms existing in airborne fine particulate matter (PM2.5) have key implications in biogeochemical cycling and human health. In this study, PM2.5 samples, collected in the typical basin cities of Xi’an and Linfen, China, were analyzed through high-throughput sequencing to understand microbial seasonal variation characteristics and ecological functions. For bacteria, the highest richness and diversity were identified in autumn. The bacterial phyla were dominated by Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes. Metabolism was the most abundant pathway, with the highest relative abundance found in autumn. Pathogenic bacteria (Pseudomonas, Acinetobacter, Serratia, and Delftia) were positively correlated with most disease-related pathways. Besides, C cycling dominated in spring and summer, while N cycling dominated in autumn and winter. The relative abundance of S cycling was highest during winter in Linfen. For fungi, the highest richness was found in summer. Basidiomycota and Ascomycota mainly constituted the fungal phyla. Moreover, temperature (T) and sulfur dioxide (SO2) in Xi’an, and T, SO2, and nitrogen dioxide (NO2) in Linfen were the key factors affecting microbial community structures, which were associated with different pollution characteristics in Xi’an and Linfen. Overall, these results provide an important reference for the research into airborne microbial seasonal variations, along with their ecological functions and health impacts.

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