Probiotics pp 57-86 | Cite as

Detection and Identification of Probiotic Microorganisms and Other Beneficial Organisms from the Human GI Tract

  • Berit Hippe
  • Jutta Zwielehner
  • Angelika Pirker
  • William M. Smith
  • Alexander G. Haslberger
Chapter
First Online:
Part of the Microbiology Monographs book series (MICROMONO, volume 21)

Abstract

Most probiotics are similar to the microorganisms naturally found in the human gastrointestinal tract, and are mainly from the genera of Lactobacillus or Bifidobacterium. Conventionally, these microorganisms have been found to be fastidious, acid-tolerant, and strictly fermentative, producing lactic and acetic acids as the major end products of sugar fermentation. Exceptions from this general description have been found to occur. In addition, interaction between probiotic microorganisms or their derivatives with the gut microbiota is now a focal point of probiotics research. This requires the characterization and enumeration of all microorganisms colonizing the gut. Molecular microbiological analysis has increased the understanding of the diversity and phylogeny of beneficial strains and their functions. Modern techniques, including genotyping methods, become increasingly important for species identification and for the differentiation of probiotic strains. The precise classification and identification of probiotic strains give a strong indication of their typical habitat and origin, safety and technical applicability, and provides possibilities for monitoring and product quality. This chapter provides an overview of probiotic strain characterization, gut metagenomics, and the analytical methods (FISH, PCR, RAPD, DGGE, repPCR, PFGE, RFLP, microarray, high throughput sequencing) required for their study.

Keywords

Lactic Acid Bacterium Terminal Restriction Fragment Length Polymorphism Probiotic Strain High Resolution Melt Probiotic Microorganism 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Berit Hippe
    • 1
  • Jutta Zwielehner
    • 1
  • Angelika Pirker
    • 1
  • William M. Smith
    • 2
  • Alexander G. Haslberger
    • 1
  1. 1.Department for Nutritional SciencesUniversity of ViennaViennaAustria
  2. 2.Crop and Food Sciences, School of LandUniversity of QueenslandBrisbaneAustralia

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