Probiotic bifidobacterial composition in accordance with secretor blood group status
A technology for bifidobacteria, microbial compositions, applied in growth and/or functional applications, capable of solving problems of high ecosystem complexity
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0072] Secretor status was determined from blood samples using standard in-house blood typing procedures of the Finnish Red Cross Blood Service. The secretor status of 59 individuals was determined, of which 48 were secretors and 7 were non-secretors. Secretor status could not be determined for 4 samples.
Embodiment 2
[0074] DGGE analysis for fecal Bifidobacterium populations was performed as described in Materials and Methods above. DGGE gel images showed that the number of bands in samples obtained from non-secretor individuals was lower than in samples from secretor individuals, suggesting that there were more Bifidobacteria genotypes present in non-secretor individuals than in secretor individuals. few. On average, non-secretors had 2.5 (up to 4) bands and secretors 5.2 bands (up to 11 bands) in the DGGE profile of bifidobacteria. Bifidobacteria were not detected in five samples (1 non-secretor sample, 4 secretor samples). Bifidobacteria information for all non-secretor individuals and selected Bifidobacteria information for secretor individuals are shown in figure 1 middle.
Embodiment 3
[0076] DGGE analysis of fecal Bifidobacteria populations was performed as described above. Principal component analysis (PCA) was performed using the tools provided in the Bionumerics software package. PCA based on the intensity of the bands detected by DGGE was used to establish coordinates for the samples and find the bands that contribute most to the principal components. DGGE gel images were analyzed using Bionumerics to perform statistical analysis across samples. PCA based on the intensity of the bands in the DGGE gel showed that samples obtained from non-secretors clustered into one group. The first and second principal components explained 56.3% of the total variance. The results are shown in figure 2 middle.
PUM
Login to View More Abstract
Description
Claims
Application Information
Login to View More 