Energy Harvesting: Some studies have suggested that a higher abundance of Firmicutes in the gut may be associated with increased energy extraction from the diet. This has led to the hypothesis that individuals with a higher ratio of Firmicutes to Bacteroidetes may be more prone to obesity. However, these associations are complex, and the relationship between gut microbiota composition and body weight is not fully understood.
Metabolism and Metabolic Disorders: Changes in the Firmicutes composition have been linked to metabolic conditions such as insulin resistance and metabolic syndrome. However, the exact mechanisms by which Firmicutes influence metabolism are still under investigation.
Inflammatory Conditions: Some Firmicutes bacteria are associated with inflammation, while others may have anti-inflammatory properties. The relationship between Firmicutes and inflammatory conditions, such as inflammatory bowel diseases (IBD), is complex and varies depending on the specific species involved.
Butyrate Production: Certain Firmicutes bacteria are known to produce short-chain fatty acids, particularly butyrate. Butyrate is considered beneficial for gut health as it serves as a primary energy source for colonocytes (cells lining the colon) and has anti-inflammatory properties. It plays a role in maintaining the health of the gut barrier.
Digestion and Nutrient Absorption: Firmicutes bacteria contribute to the digestion of complex carbohydrates and the absorption of nutrients in the gut. The breakdown of dietary fibers and other complex carbohydrates by Firmicutes can lead to the production of beneficial metabolites.
A lot more information is available when you are logged in and raise the display level
Other Sources for more information:
|Statistics||5347 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||14.15||11.3 %ile||95.544||99.6 %ile||0||82.263||40.689||21.211|
|BiomeSight||16.342||10.1 %ile||98.811||100 %ile||3.028||74.39||38.709||18.205|
|Ombre/Thryve||1.241||7 %ile||100||100 %ile||0||89.772||41.444||24.657|
|uBiome||24.525||11.7 %ile||99.822||100 %ile||9.655||88.424||49.04||20.094|
|Low Boundary||High Boundary||Low Boundary %age||High Boundary %age||Lab Samples|
|Lab||Frequency Seen||Average||Standard Deviation||Sample Count||Lab Samples|
|bugspeak||100 %||15.098 %||%||1.0||1|
|CosmosId||100 %||33.759 %||30.511 %||38.0||38|
|AmericanGut||100 %||39.174 %||26.362 %||18.0||18|
|GanzimmunDiag||100 %||43.731 %||0 %||3.0||3|
|Microba||96.667 %||34.697 %||17.787 %||29.0||30|
|BiomeSightRdp||100 %||6.869 %||14.315 %||45.0||45|
|Microba1||100 %||17.69 %||%||1.0||1|
|es-xenogene||100 %||11.542 %||18.774 %||35.0||35|
|SequentiaBiotech||100 %||37.225 %||20.935 %||36.0||36|
|Thorne||100 %||41.792 %||16.444 %||55.0||55|
|Tiny||100 %||19.17 %||%||1.0||1|
|uBiome||99.369 %||49.027 %||20.085 %||788.0||793|
|CerbaLab||100 %||41.527 %||31.202 %||3.0||3|
|Thryve||100 %||39.636 %||24.319 %||1571.0||1571|
|BiomeSight||100 %||38.638 %||18.326 %||2664.0||2664|
|custom||97.015 %||6.844 %||6.544 %||65.0||67|
|Medivere||100 %||52.811 %||6.24 %||7.0||7|
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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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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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