MethodsX (Jun 2024)

Sampling technique to pool genetic materials of microorganism communities in blue-swimming crab processing plant industry

  • Asadatun Abdullah,
  • Tati Nurhayati,
  • Fifi Gus Dwiyanti,
  • Sabila Diana Ahmad Sauqi

Journal volume & issue
Vol. 12
p. 102503

Abstract

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The crab and seafood processing industry must fulfill standard requirements for sanitation, hygiene, and good manufacturing methods to ensure the safety of the products and free from foodborne bacteria. However, equipment and processing unit surfaces are challenging to clean optimally, which can cause persistent bacteria to emerge. Eliminating persistent bacteria is the latest challenge in the fish processing industry for optimal disinfection, preventing cross-contamination, and controlling foodborne outbreaks. Microbiological testing in industry has been limited to selective culture-media techniques; thus, a rapid, sensitive, accurate, and routine applicable analytical method is urgently needed. The significant reduction in the costs of high-throughput sequencing technologies supports the possibility of routine applications in the industry. This study aimed to determine the profile of the microbial community on the surface of the production room and blue-swimming crab processing unit equipment using short-read metagenomic techniques. The analysis included the stages of sampling, bacterial incubation, bacterial DNA isolation, sequencing, and bioinformatics analysis. The first important step to increase the possibility of routine adoption in the seafood industry is to reduce the cost, complexity, and time required to complete the analysis. Therefore, in this protocol, we generate a scalable, flexible, cost-effective, and auditable workflow. • Collection of bacterial samples by swabbing the surface of the equipment using a sterile cotton swab and sterile cloth, which is easy to apply and follow in the blue-swimming crab processing plant industry. • Effective and efficient sample-pooling is an important step in identifying bacterial communities by metagenomic analysis.

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