| Micrococcales| Micrococcales Prevot 1940 (Approved Lists 1980) emend. Nouioui et al. 2018| Micrococcineae| Micrococcineae (Micrococceae Prevot 1961) emend. Stackebrandt et al. 1997| Micrococcineae Stackebrandt et al. 1997| Micrococcineae Stackebrandt et al. 1997 emend. Yassin et al. 2011| Micrococcineae Stackebrandt et al. 1997 emend. Zhi et al. 2009
Normal Skin Microbiota: Many bacteria within the Micrococcales order are part of the normal skin microbiota. Staphylococcus and Micrococcus are examples of genera within this order that are commonly found on the skin.
Role in Skin Health: Some members of Micrococcales, particularly Staphylococcus species, are considered normal inhabitants of the skin and play a role in maintaining skin health. However, certain species, such as Staphylococcus aureus, can become opportunistic pathogens and cause skin infections under certain conditions.
Infections and Opportunistic Pathogens: Some bacteria within the Micrococcales order, particularly Staphylococcus species, can be opportunistic pathogens, causing infections in various body sites. Staphylococcus aureus, for example, is known to cause skin and soft tissue infections, as well as more severe infections in other organ systems.
Antibiotic Resistance: Some Staphylococcus species, including Staphylococcus aureus, are known for their ability to develop antibiotic resistance. Methicillin-resistant Staphylococcus aureus (MRSA) is a well-known antibiotic-resistant strain that can cause difficult-to-treat infections.
Healthcare-Associated Infections: Staphylococcus species, members of the Micrococcales order, are sometimes associated with healthcare-associated infections. They can be problematic in hospital settings, causing infections in individuals with compromised immune systems or undergoing medical procedures.
The above data is from 1000 Healthy Individuals done using Shotgun(10 Millions reads) provide courtesy of Precision Biome.
A lot more information is available when you are logged in and raise the display level
Other Sources for more information:
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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 | Average | Median | Minimum | Maximum | Std.Dev. | Skew | 25 - 75 Percentile | 5 - 95 Percentile | Lab Ranges | Box-Plot-Whiskers | Harmonic Mean | Geometric Mean | Obs. |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
BiomeSight | 0.5965 | 0.025 | 0.004 | 0.001 | 9.366 | 0.2815 | 0.2243 | 0.002 - 0.008 | 0.001 - 0.042 | -0.5238 - 0.5739 | -0.007 - 0.017 | 0.0029 | 0.0046 | 2210 |
BiomeSightRdp | 0.4444 | 0.0033 | 0.0025 | 0.001 | 0.01 | 0.0026 | 0.9596 | 0.0018 - 0.004 | 0.001 - 0.0078 | -0.0017 - 0.0084 | -0.0016 - 0.0074 | 0.0021 | 0.0026 | 12 |
CosmosId | 0.6571 | 0.0235 | 0.008 | 0.001 | 0.206 | 0.05 | 0.9302 | 0.0025 - 0.0188 | 0.001 - 0.1372 | -0.074 - 0.121 | -0.022 - 0.0434 | 0.0036 | 0.0076 | 23 |
custom | 0.1702 | 0.0074 | 0.0075 | 0.0014 | 0.0172 | 0.0049 | -0.0535 | 0.0043 - 0.009 | 0.002 - 0.0143 | -0.0021 - 0.017 | -0.0028 - 0.0161 | 0.0044 | 0.0059 | 8 |
es-xenogene | 0.9545 | 0.0461 | 0.011 | 0.002 | 0.29 | 0.0757 | 1.3882 | 0.004 - 0.04 | 0.002 - 0.18 | -0.1017 - 0.1938 | -0.05 - 0.094 | 0.0068 | 0.0149 | 21 |
Medivere | 1 | 0.0334 | 0.0163 | 0.0033 | 0.0895 | 0.0378 | 1.3606 | 0.0088 - 0.0537 | 0.0037 - 0.0886 | -0.0402 - 0.1071 | -0.0587 - 0.1211 | 0.0096 | 0.0176 | 7 |
Microba | 0.24 | 0.555 | 0.258 | 0.045 | 2.33 | 0.882 | 1.0102 | 0.0775 - 0.3808 | 0.0467 - 1.8443 | -1.165 - 2.275 | -0.3774 - 0.8356 | 0.1117 | 0.2214 | 6 |
SequentiaBiotech | 0.6944 | 0.8227 | 0.9343 | 0.0104 | 2.4447 | 0.7618 | -0.4396 | 0.0591 - 1.2355 | 0.0135 - 2.3466 | -0.6628 - 2.3081 | -1.7055 - 3.0001 | 0.066 | 0.3152 | 25 |
Thorne | 0.9524 | 0.0397 | 0.021 | 0.0004 | 0.6995 | 0.0666 | 0.8382 | 0.0143 - 0.038 | 0.0064 - 0.1171 | -0.0903 - 0.1696 | -0.0214 - 0.0736 | 0.0107 | 0.0232 | 180 |
Thryve | 0.7984 | 0.0556 | 0.0071 | 0.0001 | 8.9704 | 0.3912 | 0.3722 | 0.0032 - 0.0169 | 0.0014 - 0.125 | -0.7072 - 0.8185 | -0.0173 - 0.0374 | 0.004 | 0.0086 | 990 |
uBiome | 0.2839 | 0.1069 | 0.0072 | 0.0018 | 4.2969 | 0.4239 | 0.7054 | 0.0031 - 0.0252 | 0.0021 - 0.3934 | -0.7196 - 0.9335 | -0.0301 - 0.0584 | 0.0052 | 0.0115 | 224 |
Source of Ranges | Low Boundary | High Boundary | Low Boundary %age | High Boundary %age |
---|---|---|---|---|
PrecisionBiome | 0.0003601268108468503 | 0.016160089522600174 | 0 | 0 |
Thorne (20/80%ile) | 140.16 | 380.48 | 0.014 | 0.038 |
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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.
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