| Erysipelotrichales| Erysipelotrichales Ludwig et al. 2010
Gut Microbiota Composition: Members of the order Erysipelotrichales are found in the human gut microbiota. The gut microbiota, which consists of trillions of microorganisms, plays a crucial role in various aspects of human health, including digestion, metabolism, and immune function.
Association with Diet: Changes in the abundance of Erysipelotrichales have been associated with dietary patterns. For example, some studies have observed an increase in Erysipelotrichales in response to high-fat diets, especially in the context of obesity.
Metabolic Health: There is some evidence to suggest that alterations in the abundance of Erysipelotrichales may be linked to metabolic conditions, such as obesity and metabolic syndrome. However, the relationship between Erysipelotrichales and metabolic health is complex, and more research is needed to understand the specific mechanisms involved.
Inflammatory Bowel Diseases (IBD): Changes in the composition of the gut microbiota, including alterations in Erysipelotrichales abundance, have been reported in individuals with inflammatory bowel diseases (IBD) such as Crohn's disease and ulcerative colitis. The role of Erysipelotrichales in the development or progression of IBD is still an area of investigation.
Association with Liver Diseases: Some studies have suggested a potential link between the abundance of Erysipelotrichales and liver diseases, including non-alcoholic fatty liver disease (NAFLD). However, more research is needed to establish the nature of this association and its implications for health.
A lot more information is available when you are logged in and raise the display level
Other Sources for more information:
Statistics | 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 | Frequency | UD-Low | UD-High | KM Low | KM High | Lab Low | Lab High | Mean | Median | Standard Deviation | Box Plot Low | Box Plot High | KM Percentile Low | KM Percentile High |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Other Labs | 7.55 | 0 | 0 | 1 | 74190 | 0 | 24451 | 5787.7 | 2760 | 9522.1 | 0 | 8240 | 0 %ile | 100 %ile |
biomesight | 93.59 | 210 | 8420 | 1050 | 8750 | 0 | 28127 | 6446.7 | 3459 | 11061.4 | 0 | 9981 | 10.9 %ile | 90.9 %ile |
thorne | 100 | 577 | 13265 | 0 | 8821 | 3772.8 | 3334 | 2575.8 | 1520 | 5174 | 0 %ile | 100 %ile | ||
thryve | 99.91 | 1399 | 25234 | 2385 | 19137 | 0 | 71813 | 15142.6 | 7558 | 28913.5 | 0 | 23120 | 10.7 %ile | 90.6 %ile |
ubiome | 99.24 | 1026 | 21098 | 1969 | 42479 | 0 | 45556 | 11507.2 | 7629 | 17372.1 | 0 | 20189 | 10.7 %ile | 97.2 %ile |
Source of Ranges | Low Boundary | High Boundary | Low Boundary %age | High Boundary %age |
---|---|---|---|---|
Thorne (20/80%ile) | 471.5 | 1349 | 0.0472 | 0.1349 |
Lab | Frequency Seen | Average | Standard Deviation | Sample Count | Lab Samples |
---|---|---|---|---|---|
AmericanGut | 93.333 % | 0.505 % | 0.622 % | 14.0 | 15 |
BiomeSight | 99.86 % | 0.651 % | 1.081 % | 2860.0 | 2864 |
BiomeSightRdp | 100 % | 0.148 % | 0.146 % | 32.0 | 32 |
bugspeak | 100 % | 0.476 % | % | 1.0 | 1 |
CerbaLab | 100 % | 1.96 % | 2.123 % | 3.0 | 3 |
CosmosId | 96.875 % | 1.215 % | 1.595 % | 31.0 | 32 |
custom | 37.288 % | 0.478 % | 0.936 % | 22.0 | 59 |
es-xenogene | 86.207 % | 0.163 % | 0.149 % | 25.0 | 29 |
Medivere | 100 % | 0.801 % | 0.628 % | 7.0 | 7 |
Microba | 71.429 % | 0.415 % | 0.313 % | 20.0 | 28 |
Microba1 | 100 % | 0.49 % | % | 1.0 | 1 |
SequentiaBiotech | 100 % | 0.353 % | 0.591 % | 36.0 | 36 |
Thorne | 85.556 % | 0.291 % | 0.244 % | 77.0 | 90 |
Thryve | 99.928 % | 1.519 % | 2.818 % | 1382.0 | 1383 |
Tiny | 100 % | 1.958 % | % | 1.0 | 1 |
uBiome | 98.864 % | 1.152 % | 1.737 % | 783.0 | 792 |
Click on Impact for information if high or low levels are causing the impact
Magnitude | Impact | Symptom |
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And display level must be raised above public.
Data comes from FoodMicrobionet. For the meaning of weight, see that site. The bacteria does not need to be alive to have an effect.
This is an Academic site. It generates theoretical models of what may benefit a specific microbiome results.
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