| Clostridium thermoautotrophicum group| cluster VII| Moorella group
Biotechnological applications: Many species within the Moorella group possess unique metabolic capabilities that make them valuable in various biotechnological processes. For example, they are involved in the conversion of carbon monoxide (CO) and hydrogen (H2) to acetate through the Wood-Ljungdahl pathway, a process known as syngas fermentation. This metabolic feature has applications in biofuel production, bioremediation, and the synthesis of valuable chemicals.
Gut microbiota: Some species within the Moorella group have been identified in the gut microbiota of humans and other animals. While their specific roles in the gut microbiome and their interactions with the host are not well-understood, they may contribute to the fermentation of complex carbohydrates and the production of short-chain fatty acids (SCFAs) in the colon. SCFAs play important roles in gut health, energy metabolism, and immune regulation.
Hydrogen production: Certain members of the Moorella group are capable of producing hydrogen gas (H2) as a metabolic byproduct during fermentation. Hydrogen production by these bacteria has potential applications in biohydrogen production, which is a promising renewable energy source.
Thermophilic environments: The Moorella group is often found in thermophilic environments such as hot springs, geothermal areas, and deep-sea hydrothermal vents. While these environments are not directly relevant to human health, studying the metabolic pathways and physiological adaptations of Moorella species in extreme conditions provides insights into their ecological roles and biotechnological potential.
Methanogenesis: Some species within the Moorella group are involved in methanogenesis, the biological production of methane gas (CH4). Methanogenic archaea often coexist with bacteria such as Moorella in anaerobic environments and form syntrophic relationships. Methane production by these microbes has implications for carbon cycling in natural ecosystems and anaerobic digestion processes.
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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 |
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Other Labs | 1.02 | 4 | 530 | 0 | 479 | 141.2 | 50 | 172.5 | 0 | 290 | 0 %ile | 100 %ile | ||
biomesight | 75.4 | 0 | 220 | 10 | 1850 | 0 | 1893 | 354.7 | 140 | 784.8 | 0 | 520 | 0 %ile | 97.5 %ile |
thorne | 100 | 2 | 50 | 0 | 43 | 17.6 | 10 | 12.8 | 8 | 38 | 0 %ile | 100 %ile | ||
thryve | 3.97 | 6 | 370 | 0 | 152 | 34.8 | 20 | 59.8 | 4 | 40 | 0 %ile | 100 %ile |
Source of Ranges | Low Boundary | High Boundary | Low Boundary %age | High Boundary %age |
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Lab | Frequency Seen | Average | Standard Deviation | Sample Count | Lab Samples |
---|---|---|---|---|---|
BiomeSight | 42.575 % | 0.036 % | 0.078 % | 1981.0 | 4653 |
BiomeSightRdp | 64.516 % | 0.048 % | 0.071 % | 20.0 | 31 |
CerbaLab | 66.667 % | 0.002 % | 0.001 % | 2.0 | 3 |
custom | 2.632 % | 0.026 % | 0.036 % | 2.0 | 76 |
es-xenogene | 15.625 % | 0.007 % | 0.003 % | 5.0 | 32 |
Medivere | 12.5 % | 0.002 % | % | 1.0 | 8 |
Thorne | 18.339 % | 0.001 % | 0.001 % | 53.0 | 289 |
Thryve | 3.5 % | 0.005 % | 0.011 % | 54.0 | 1543 |
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