Diversity of spoilage fungi in dairy products and environment, and their resistance to chemical preservatives

Fungal spoilage is one of the causes of consequential losses in the dairy industry. In this context, the use of bioprotective cultures can be an alternative or a complementary approach to be considered. Lactic acid bacteria (LAB) and propionibacteria, as well as some fungal species, can exhibit antifungal activities with large differences in activity between strains. Therefore, it is necessary to develop high-throughput screening methods to test a large number of strains and find the most efficient ones. In the present study, we developed a miniaturized high-throughput screening technique to rapidly detect antifungal activities in a cheese-like model. This model, distributed in a 24-well plate, consisted of 5-fold concentrated whole milk ultrafiltration retentate (final fat concentration of 45%), rennet (0.03%) and inoculated with a mesophilic lactic commercial starter and a pH indicator. Each well of the plate could be considered as a miniature cheese of ~2 g. Potent antifungal isolates were cultured in two dairy media; (i) a 10%-reconstituted low heat skim milk supplemented with 45% anhydrous milk fat (LH) and (ii) a 6-fold concentrated milk ultrafiltration permeate sterilized by 0.22 μm filtration and complemented with 10 g/l yeast extract and a pH indicator (UF). After cultivation, cultures (100 µl) were deposited on the miniature cheese surfaces followed by inoculation in duplicate with 50 spores or cells of 4 different fungal targets (1 fungi/plate), e.g., Mucor racemosus, Galactomyces geotrichum, Penicillium commune and Yarrowia lipolytica, and incubation at 12°C for up to 15 days. We screened 505 bacterial isolates belonging to Lactobacillus, Lactococcus, Pediococcus, Leuconostoc and Propiobacterium genera and 198 fungal isolates belonging to 28 genera. This high-throughput screening for antifungal activity revealed that 52 and 216 bacteria, and, 53 and 89 fungi, inhibited at least one fungal target after cultivation in UF and LH, respectively. Among the 4 tested fungal targets, P. commune was the most frequently inhibited fungus while only few isolates were able to inhibit M. racemosus or Y. lipolytica. This method opens new possibilities to screen microorganisms for antifungal activities. These results also underline the importance of the culture and screening media used on the expression of antifungal activities by bacteria or fungi

High-throughput screening for antifungal activities of bacterial and fungal isolates in a cheese-like medium.

Fungal spoilage is one of the causes of consequential losses in the dairy industry. In this context, the use of bioprotective cultures can be an alternative or a complementary approach to be considered. Lactic acid bacteria (LAB) and propionibacteria, as well as some fungal species, can exhibit antifungal activities with large differences in activity between strains. Therefore, it is necessary to develop high-throughput screening methods to test a large number of strains and find the most efficient ones. In the present study, we developed a miniaturized high-throughput screening technique to rapidly detect antifungal activities in a cheese-like model. This model, distributed in a 24-well plate, consisted of 5-fold concentrated whole milk ultrafiltration retentate (final fat concentration of 45%), rennet (0.03%) and inoculated with a mesophilic lactic commercial starter and a pH indicator. Each well of the plate could be considered as a miniature cheese of ~2 g. Potent antifungal isolates were cultured in two dairy media; (i) a 10%-reconstituted low heat skim milk supplemented with 45% anhydrous milk fat (LH) and (ii) a 6-fold concentrated milk ultrafiltration permeate sterilized by 0.22 μm filtration and complemented with 10 g/l yeast extract and a pH indicator (UF). After cultivation, cultures (100 µl) were deposited on the miniature cheese surfaces followed by inoculation in duplicate with 50 spores or cells of 4 different fungal targets (1 fungi/plate), e.g., Mucor racemosus, Galactomyces geotrichum, Penicillium commune and Yarrowia lipolytica, and incubation at 12°C for up to 15 days. We screened 505 bacterial isolates belonging to Lactobacillus, Lactococcus, Pediococcus, Leuconostoc and Propiobacterium genera and 198 fungal isolates belonging to 28 genera. This high-throughput screening for antifungal activity revealed that 52 and 216 bacteria, and, 53 and 89 fungi, inhibited at least one fungal target after cultivation in UF and LH, respectively. Among the 4 tested fungal targets, P. commune was the most frequently inhibited fungus while only few isolates were able to inhibit M. racemosus or Y. lipolytica. This method opens new possibilities to screen microorganisms for antifungal activities. These results also underline the importance of the culture and screening media used on the expression of antifungal activities by bacteria or fungi

Expression profile of the target genes SvAP3/PI and SvPEPC.

<p>The plot corresponding to the expression profile of the MADS-box gene SvAP3/PI (magenta bars) and the enzyme SvPEPC (green bars) responsible for the initial carbon fixation on C4 photosynthesis is shown in (A). The developmental dataset was normalized using the Si034613 and Si035045 genes. It can be observed in (B) that the expression profile of SvPEPC on the leaf gradient was normalized using the gene pair that included Si021373 and Si034613. This result is compared with the transcriptome data (light blue line) for the same gene (personal communication with Todd Mockler). The small plots correspond to the same described target genes normalized with the poorly ranked reference genes: Si018607 and Si025395 for the developmental set and Si000245 and Si018607 for leaf gradient. The reference samples are indicated with an asterix.</p

RNA integrity profile.

<p>The assessment of the best methodology for RNA extraction for each representative tissue: seedling (A); shoot (B); root (C), inflorescence (D) and axis (E). Electropherograms were obtained using an Agilent 2100 Bioanalyzer. RNA quality is expressed as the RNA integrity number (RIN).</p

Candidate genes and their primer sequences that were selected for evaluation of expression stability using qPCR analysis on <i>S</i>. <i>viridis</i> tissues, and the sequences of two genes of interest.

<p>¹Score and identity values assessed through alignment between S. italica sequences and S. viridis sequences (TM personal communication). NA indicates non-available data due to missing sequence of S. viridis</p><p>Candidate genes and their primer sequences that were selected for evaluation of expression stability using qPCR analysis on <i>S</i>. <i>viridis</i> tissues, and the sequences of two genes of interest.</p

Candidate genes ranked by geNorm algorithm according to their average pairwise variation compared with all other genes.

<p>Stability values are listed from the most stable to the least stable.</p><p>Candidate genes ranked by geNorm algorithm according to their average pairwise variation compared with all other genes.</p

geNorm results for expression stability values (M) and ranking of the candidate reference genes.

<p>Average expression stability values (M) of the reference genes measured during geNorm stepwise exclusion of the least stable reference genes. Both the developmental (A) and leaf gradient (B) datasets are shown; lower values of average expression stability, M, indicate more stable expression.</p

Optimal number of control genes for an accurate normalization.

<p>The geNorm pairwise variation <i>V</i>_{<i>n</i>(<i>n</i>+1)} was analyzed between the normalization factors (NF) for both developmental (A) and leaf gradient (B) datasets. All values are below the cutoff of 0.15.</p