An Iterative Sensory Procedure to Select Odor-Active Associations in Complex Consortia of Microorganisms: Application to the Construction of a Cheese Model

Abstract

The aim of this study was to develop and validate an iterative procedure based on odor assessment to select odor-active associations of microorganisms from a starting association of 82 strains (G1), which were chosen to be representative of Livarot cheese biodiversity. A 3-step dichotomous procedure was applied to reduce the starting association G1. At each step, 3 methods were used to evaluate the odor proximity between mother (n strains) and daughter (n/2 strains) associations: a direct assessment of odor dissimilarity using an original bidimensional scale system and 2 indirect methods based on comparisons of odor profile or hedonic scores. Odor dissimilarity ratings and odor profile gave reliable and sometimes complementary criteria to select G3 and G4 at the first iteration, G31 and G42 at the second iteration, and G312 and G421 at the final iteration. Principal component analysis of odor profile data permitted the interpretation at least in part, of the 2D multidimensional scaling representation of the similarity data. The second part of the study was dedicated to 1) validating the choice of the dichotomous procedure made at each iteration, and 2) evaluating together the magnitude of odor differences that may exist between G1 and its subsequent simplified associations. The strategy consisted of assessing odor similarity between the 13 cheese models by comparing the contents of their odor-active compounds. By using a purge-and-trap gas chromatography-olfactory/mass spectrometry device, 50 potent odorants were identified in models G312, G421, and in a typical Protected Denomination of Origin Livarot cheese. Their contributions to the odor profile of both selected model cheeses are discussed. These compounds were quantified by purge and trap-gas chromatography-mass spectrometry in the 13 products and the normalized data matrix was transformed to a between-product distance matrix. This instrumental assessment of odor similarities allowed validation of the choice of G312 as the best 10-strain ecosystem.

Bacterial-Fungal Interactions: Hyphens between Agricultural, Clinical, Environmental, and Food Microbiologists

“…They utilize lactate and thus deacidify the cheese surface, enabling the establishment of less-acid-tolerant bacterial communities, which play a significant role in the quality and safety of the final product (79). To understand the BFIs that occur during ripening, Bonaiti et al (47) developed a microbial Livarot cheese model by selecting microbial associations contributing to cheese aroma. They succeeded in simplifying an ecosystem of 83 microbial strains from a commercial Livarot cheese to a subecosystem composed of nine species that had a strong similarity to that of the commercial cheese.…”

Biodiversity in sulfur metabolism in hemiascomycetous yeasts

“…Some studies have revealed that yeasts transform sulfur amino acids into characteristic volatile sulfur compounds (VSC) that have a considerable impact on food flavor, notably in wine (Perpète et al , 2006) and cheese (Bonaïti et al , 2005). Sulfur metabolism has not been extensively studied in the hemiascomycete phylum, except in S. cerevisiae .…”

Diversity, Dynamics and Functional Role of Actinomycetes on European Smear Ripened Cheeses

“…All these attributes contribute to defi ne cheese quality and safety and there is a need to understand how they are regulated. Bonaiti et al ( 2005 ) showed for the fi rst time an iterative procedure based on odour assessment to select odour-active associations of microorganisms in cheese microcosms. In order to study microbial interactions within a cheese microcosm further, they built model microbial communities generating odour comparable to that of Livarot cheese.…”

“…Iterative procedure for selection of odour-active microbial communities of microorganisms in cheese (Adapted fromBonaiti et al 2005 ). Selected daughter communities are shaded in blue (Color fi gure online)…”