Recent advances in molecular techniques to study microbial communities in food-associated matrices and processes

A. Justé, B.P.H.J. Thomma, B. Lievens

Research output: Contribution to journalArticleAcademicpeer-review

179 Citations (Scopus)

Abstract

In the last two decades major changes have occurred in how microbial ecologists study microbial communities. Limitations associated with traditional culture-based methods have pushed for the development of culture-independent techniques, which are primarily based on the analysis of nucleic acids. These methods are now increasingly applied in food microbiology as well. This review presents an overview of current community profiling techniques with their (potential) applications in food and food-related ecosystems. We critically assessed both the power and limitations of these techniques and present recent advances in the field of food microbiology attained by their application. It is unlikely that a single approach will be universally applicable for analyzing microbial communities in unknown matrices. However, when screening samples for well-defined species or functions, techniques such as DNA arrays and real-time PCR have the potential to overtake current culture-based methods. Most importantly, molecular methods will allow us to surpass our current culturing limitations, thus revealing the extent and importance of the `non-culturable¿ microbial flora that occurs in food matrices and production.
Original languageEnglish
Pages (from-to)745-761
JournalFood Microbiology
Volume25
Issue number6
DOIs
Publication statusPublished - 2008

Keywords

  • 16s ribosomal-rna
  • restriction-fragment-length
  • in-situ hybridization
  • gradient gel-electrophoresis
  • real-time pcr
  • strand-conformation polymorphism
  • lactic-acid bacteria
  • intergenic spacer analysis
  • culture-independent methods
  • single nucleotide polymorp

Fingerprint

Dive into the research topics of 'Recent advances in molecular techniques to study microbial communities in food-associated matrices and processes'. Together they form a unique fingerprint.

Cite this