Fermentation in Food Production: Weissella species are commonly used in the fermentation of foods, contributing to the development of specific flavors and textures in fermented products. These bacteria are often part of the natural microbiota involved in processes like sourdough fermentation and vegetable fermentation.
Probiotic Potential: Some strains of Weissella have been investigated for their potential probiotic properties. Probiotics are live microorganisms that, when administered in adequate amounts, confer health benefits to the host. Certain Weissella strains have shown potential in vitro and in animal studies for promoting gut health and exerting antimicrobial activity against pathogenic bacteria.
Immunomodulation: Like other LAB, Weissella species may have immunomodulatory effects. Research suggests that LAB can interact with the immune system and modulate its responses, potentially influencing the balance of the immune system.
Antimicrobial Properties: Weissella strains have been studied for their antimicrobial properties, which may contribute to the inhibition of pathogenic bacteria in the gut. This property could be beneficial for overall gut health.
Diversity of Strains: It's important to note that the effects of different Weissella strains can vary, and not all strains may have the same probiotic or health-promoting properties.
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Other Sources for more information:
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5735 Interactions with Other Bacteria | NCBI | Data Punk | End Products Produced |
Different labs use different software to read the sample. See this post for more details.
One lab may say you have none, another may say you have a lot! - This may be solely due to the software they are using to estimate.
We deem lab specific values using values from the KM method for each specific lab to be the most reliable.
Lab Low and High are calculated using the formula that most labs use: Mean - 2 Standard Deviation to Mean + 2 Standard Deviation
Lab | KM Low | KM Percentile Low | KM High | KM Percentile High | Lab Low | Lab High | Mean | Standard Deviation |
---|---|---|---|---|---|---|---|---|
All | 0.001 | 8.8 %ile | 0.036 | 96.3 %ile | 0 | 0.505 | 0.024 | 0.245 |
BiomeSight | 0.001 | 0 %ile | 0.024 | 96.2 %ile | 0 | 0.277 | 0.016 | 0.133 |
Ombre/Thryve | 0.002 | 8.6 %ile | 0.043 | 95.6 %ile | 0 | 0.681 | 0.03 | 0.332 |
uBiome | 0.002 | 0 %ile | 0.469 | 100 %ile | 0 | 0.243 | 0.044 | 0.102 |
Low Boundary | High Boundary | Low Boundary %age | High Boundary %age | Lab Samples |
---|---|---|---|---|
1000 | 10000 | 0.1 | 1 | XenoGene |
Lab | Frequency Seen | Average | Standard Deviation | Sample Count | Lab Samples |
---|---|---|---|---|---|
CosmosId | 2.632 % | 0.009 % | % | 1.0 | 38 |
es-xenogene | 57.143 % | 0.277 % | 1.032 % | 20.0 | 35 |
SequentiaBiotech | 11.111 % | 0.015 % | 0.002 % | 4.0 | 36 |
Thorne | 100 % | 0.001 % | 0.001 % | 55.0 | 55 |
uBiome | 3.783 % | 0.044 % | 0.102 % | 30.0 | 793 |
CerbaLab | 66.667 % | 0.002 % | 0.001 % | 2.0 | 3 |
Thryve | 65.5 % | 0.039 % | 0.394 % | 1029.0 | 1571 |
BiomeSight | 53.494 % | 0.015 % | 0.125 % | 1424.0 | 2662 |
custom | 13.433 % | 0.023 % | 0.008 % | 9.0 | 67 |
Medivere | 42.857 % | 0.003 % | 0.002 % | 3.0 | 7 |
BiomeSightRdp | 33.333 % | 0.069 % | 0.253 % | 15.0 | 45 |
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All suggestions are computed solely on their predicted microbiome impact. Safety, side-effects etc must be evaluated by your medical professionals before starting. Some items suggests have significant risk of adverse consequences for some people.
Special thanks to David F Morrison and Geert Van Houcke for doing Quality Assurance. Special thanks to Oliver Luk, B.Sc. (Biology) from BiomeSight for spot checking the coding of data from the US National Library of Medicine
This is an Academic site. It generates theoretical models of what may benefit a specific microbiome results.
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Use of data on this site is prohibited except under written license. There is no charge for individual personal use. Use for any commercial applications or research requires a written license.
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