A reader asked about what we know. They were looking for food for a child that may inhibit these by inhibiting the bacteria that provides them with the metabolites to flourish. These two have a high prevalence with ME/CFS.
We need to be aware that there may be a ‘mafia family’ in operation, for example: “HIV also acts synergistically with multiple other viruses, such as HPV, EBV, varicella zoster virus (VZV), and HHV-8. ” 
Unfortunately available literature on PubMed contains few human studies.
- Lower Prevotella,Mycoplasma pneumoniae, Staphylococcus epidermidis, and Staphylococcus aureus 
The reader had uploaded a microbiome from Thryve and I wanted to see how severe mycoplasma was:
My intent was to see if there were any statistically significant association with other bacteria (friend or foe analysis).
Drilling down to the species level, we find that he numbers were not abnormal (below average but at median)
Concerning HHV virus — that is outside of the scope of my analysis site. There is no published literature to work from. I do have a personal belief that HHV and other virus reactivation is a side effect of microbiome dysfunction. Yes, some antivirals help — but those same antivirals also alter the microbiome leaving these antiviral mechanism of action unclear.
Returning to the person
- The reader child “he still have learning disabilities”. I looked at Naive Predicted Symptoms with their microbiome and with a score of 1.0 (highest), we have these predicted that match this description (25 possible of 5200 pairs possible). HHV6 and Mycoplasma were included in the symptom list! (this does not mean the child has them — rather that people who were told or believed they had them; self reporting and not a lab test)
- Infection: Mycoplasma|Neurological-Vision: Blurred Vision|
- DePaul University Fatigue Questionnaire : Impaired Memory & concentration|Neurological: emotional overload|
- DePaul University Fatigue Questionnaire : Impaired Memory & concentration
I proceeded to pick the bacteria (clicking the checkboxes above) that matched these symptoms and built a custom profile. The result was that many bacteria recurred in different combinations, so we ended up with just 9.
Running it through the suggestions machine learning we got:
The above are suggestions from a machine learning algorithm. They should be reviewed and discussed with your medical professional before starting.
The goal was to modify diet to help with the symptoms. We were not able to find anything based on the presumed cause in conventional medical literature. We were able to identify some specific bacteria shifts that corresponded to reported symptoms and get diet suggestions from those.