Butyrate Production: Faecalibacterium prausnitzii is known for its ability to produce butyrate, a short-chain fatty acid (SCFA). Butyrate serves as a vital energy source for the cells lining the colon, contributing to their health and integrity. It has anti-inflammatory properties and helps maintain gut barrier function.
Anti-inflammatory Effects: Butyrate produced by Faecalibacterium prausnitzii has potent anti-inflammatory properties that can help modulate the immune response in the gut. It can regulate the production of inflammatory molecules, potentially reducing gut inflammation and contributing to the management of inflammatory conditions like inflammatory bowel diseases (IBD).
Gut Health: Faecalibacterium prausnitzii plays a role in promoting overall gut health by contributing to the maintenance of a balanced gut microbiota. Its abundance in the gut has been associated with a healthier gut environment, potentially reducing the risk of gastrointestinal disorders and supporting gut barrier function.
Immune Modulation: This bacterium has been suggested to have immunomodulatory effects, influencing the immune system's function beyond the gut. It may contribute to a balanced immune response and could have implications in managing immune-related conditions.
Metabolic Health: Some research suggests that Faecalibacterium prausnitzii abundance might be associated with improved metabolic health. Higher levels of this bacterium have been correlated with better glucose metabolism and lower levels of markers related to metabolic disorders, such as insulin resistance.
Disease Associations: Alterations in the abundance of Faecalibacterium prausnitzii have been observed in various diseases, including inflammatory bowel diseases (IBD), irritable bowel syndrome (IBS), and metabolic disorders. However, its exact role in these conditions and whether the changes observed are causal or consequential remain areas of ongoing research.
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Other Sources for more information:
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5884 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 | 0.074 | 4.8 %ile | 33.353 | 98.7 %ile | 0 | 26.794 | 10.531 | 8.297 |
BiomeSight | 0.078 | 4.2 %ile | 33.353 | 98.6 %ile | 0 | 28.151 | 11.762 | 8.362 |
Ombre/Thryve | 0.109 | 6.9 %ile | 46.458 | 100 %ile | 0 | 28.816 | 11.546 | 8.811 |
uBiome | 0.002 | 0 %ile | 22.914 | 99 %ile | 0 | 16.363 | 6.075 | 5.249 |
Low Boundary | High Boundary | Low Boundary %age | High Boundary %age | Lab Samples |
---|---|---|---|---|
100000 | 150000 | 10 | 15 | JasonH |
19000 | 50000 | 1.9 | 5 | Medivere |
12100 | 57900 | 1.21 | 5.79 | Nirvana/CosmosId |
20000 | 150000 | 2 | 15 | XenoGene |
Lab | Frequency Seen | Average | Standard Deviation | Sample Count | Lab Samples |
---|---|---|---|---|---|
bugspeak | 100 % | 46.907 % | % | 1.0 | 1 |
CosmosId | 92.105 % | 3.058 % | 1.894 % | 35.0 | 38 |
Microba | 20 % | 2.393 % | 1.758 % | 6.0 | 30 |
GanzimmunDiag | 100 % | 0.896 % | 0 % | 3.0 | 3 |
es-xenogene | 97.143 % | 3.622 % | 2.015 % | 34.0 | 35 |
SequentiaBiotech | 94.444 % | 6.924 % | 6.619 % | 34.0 | 36 |
Thorne | 100 % | 8.641 % | 5.099 % | 55.0 | 55 |
Tiny | 100 % | 0.064 % | % | 1.0 | 1 |
uBiome | 91.929 % | 6.075 % | 5.246 % | 729.0 | 793 |
CerbaLab | 100 % | 0.479 % | 0.463 % | 3.0 | 3 |
Thryve | 99.236 % | 11.677 % | 8.704 % | 1559.0 | 1571 |
BiomeSight | 99.625 % | 11.722 % | 8.356 % | 2654.0 | 2664 |
custom | 55.224 % | 2.828 % | 2.877 % | 37.0 | 67 |
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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.
Copyright 2016-2023 Lassesen Consulting, LLC [2007], DBA, Microbiome Prescription. All rights served.
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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.
Caveat emptor: Analysis and suggestions are based on modelling (and thus infererence) based on studies. The data sources are usually given for those that wish to consider alternative inferences. theories and models.
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