An ME/CFS Journey using their Microbiome

Back Story

I go this email from someone who just moved to Spain from the U.S. She has being using Microbiome Prescription to try improving her ME/CFS. She had the testing done by Ombre Labs, and then transfer the data to BiomeSight. This allows her to keep consistent analysis on her journey of recovery.

I’m doing pretty well with bacillus coagulans and pretty bad with some other recommendations so I’m looking for some extra clarity. When I hit a great herbal antibiotic and a great probiotic life gets so much better, but oftentimes it’s harder than that. Sometimes I don’t get enough  herbal antibiotic recommendations. Some of the probiotics I may need, like e-coli or bifidus, cannot sustain me the way coagulans does -keeping my local infections at bay. So I try to combine them  or if it’s not clear if they are compatible, I tend to not take them, which is a shame. So I’m considering prescription medicine to see if I can get a bit more help.

I’m also figuring out where to buy supplements etc. Life is really an adventure!

Comparison Between Samples And Lab Interpretations

For those not familiar with the issue of Lab Interpretation of the identical data see The taxonomy nightmare before Christmas…[2019]. Ombre typically reports on 25-30% more bacteria types than BiomeSight. The quality improved, but the number of bacteria identified are very similar. I give observations below:

OmbreLabResultsBiomeSight LabResults
Lab Read Quality2.
Bacteria Reported By Lab365628625280497490
Bacteria Over 99%ile560271
Bacteria Over 95%ile27241193111
Bacteria Over 90%ile49511375824
Bacteria Under 10%ile18604854562224
Bacteria Under 5%ile10284112830175
Bacteria Under 1%ile17317113135
Lab: Thryve
Rarely Seen 1%091042
Rarely Seen 5%8402741817
Outside Range from Medivere16165444
Outside Range from Metagenomics7719171716
Outside Range from MyBioma14148777
Outside Range from Nirvana/CosmosId23238997
Outside Range from XenoGene333325222219
Outside Lab Range (+/- 1.96SD)101442282822
Outside Box-Plot-Whiskers6461126137
Outside Kaltoft-Moldrup11218231708464
Condition Est. Over 99%ile0054270113175
Condition Est. Over 95%ile000010
Condition Est. Over 90%ile2210040
Enzymes Over 99%ile131517060
Enzymes Over 95%ile698200100
Enzymes Over 90%ile155411022320
Enzymes Under 10%ile551382455121
Enzymes Under 5%ile22671593308219212
Enzymes Under 1%ile521320187132146
Compounds Over 99%ile104126641124767
Compounds Over 95%ile385397430719
Compounds Over 90%ile5335486011276138
Compounds Under 10%ile183248103342313323
Compounds Under 5%ile109127359180125224
Compounds Under 1%ile1617303376473
Compounds Under 1%ile1721224172140
Comparison Table

The following are apparent, between the last two samples, the reader was trying to follow the suggestions.

  • The number of high bacteria (> 90%ile, > 95%ile, > 99%ile) show significant decline
  • Rarely Seen bacteria show significant decline
  • The number of low bacteria (< 10%ile, < 5%ile, < 1%ile) show significant increases – suggesting more diversity
  • The Outside Range is a little mixed, with either both labs showing a decline, OR one showing a decline and one an increase. None showed increase on both.
  • High Enzymes show decline. Low Enzymes had inconsistent results.
  • Compounds and Conditions had inconsistent results

Enzymes, Compounds and Conditions are best effort estimates (and experimental) and be taken with a grain of salt (50 mg). By conventional thinking, the microbiome has improved (less extreme high levels), less pathogenic bacteria types.

Going Forward

Consensus approach (also known as Monte Carlo Simulation) remains the safest choice. To simplify the analysis, I will use the standard triplet (Outside Lab Range, Box-Plot-Whiskers, Kaltoft-Moldrup) on both latest samples processed through Ombre and Biomesight data processing. Given the report that some did not work subjectively, I decided to proceed down the most restrictive approach. I used the new quick suggestions (best choice for someone with brain fog).


The #1 and #2 choices are lactobacillus paracasei and bacillus subtilis. Kegg choices are Escherichia coli, Bacillus subtilis (with Biomesight numbers being much less than Ombres).

Microbiome ModifierSuggestionsClinical DosageEst ConfidenceSuggestionsEst Confidence
bacillus subtilisTake10 BCFU/day340.4Take223.6
bacillus lichenformisTake279.1Take20.9
enterococcus faeciumTake1 BCFU/day13.2Take8
bifidobacterium longumTake10 BCFU/day516.2Take182.5
lactobacillus paracaseiTake40 BCFU/day58.7Take397.5
pediococcus acidilacticiTake157.7Take215.4
Items with Agreement

For other items, there were a surprisingly few in agreement.

Microbiome ModifierSuggestionsClinical DosageEst ConfidenceSuggestionsClinical DosageEst Confidence
galactooligosaccharides (GOS)Take10 gm/day15Take10 gm/day139.1
CalciumTake500 mg/day129.2Take500 mg/day36.2
MagnesiumTake500 mg/day189.7Take500 mg/day119.2
D-RiboseTake10 gm/day80.6Take10 gm/day23.6
GlycineTake15 gm/day409.2Take15 gm/day258.5
Omega-3 fatty acidsTake4 gm/day166.8Take4 gm/day289.4

Using the Consensus across Multiple Samples

This gives a lot more information, but at the cost of more complexities.

The approach is similar to the above, except for suggestions we change to Every thing. I have extracted the items > 100 that are 5 or 6 Take Count with 0 or 1 Avoid Count to the table below in decreasing order

Prescription Drugs Analysis

The approach is similar to the above, except for suggestions we change to Every thing.

And then use the option on the Multiple Samples tab,

Remember to empty the old baskets.

The items that came up (as discussed above) are:

So every item at the top of the list (from over a possible choice of 3000 different prescription drugs), are cross-validated against the literature with the exception of proton-pump-inhibitor. This person can show their medical professional that the microbiome model suggests it and clinical studies confirm that they are reasonable.

I favor Dr. Cecile Jadin protocol of rotating antibiotics typically a course (7-10 days), then a break of 1-2 weeks, and then proceed to the next one.

Feedback from Reader

I love Dr. AI [Artificial Intelligence], which other doctor asks you to eat as much 100% chocolate I can??? And I tolerate it, luckily. And there are so many yummy brands in Spain, I don’t remember having that much choice when I left! 

Thanks for all the info, very helpful, very encouraging to see progress “on paper”, and to have clear things to share with my new doctor. I’m confident I’ll find a microbiome helper here in Barcelona.

The greatest challenge in treating ME/CFS is that there is no clear test to see if something is helping. Using repeated microbiome samples with systematic trials of suggestions, provides objective evidence — even when the subjective evidence is not pronounced. ME/CFS patients have a real challenge on doing subjective evaluation — they often cannot recall how they were two weeks ago!

Postscript – and Reminder

I am not a licensed medical professional and there are strict laws where I live about “appearing to practice medicine”.  I am safe when it is “academic models” and I keep to the language of science, especially statistics. I am not safe when the explanations have possible overtones of advising a patient instead of presenting data to be evaluated by a medical professional before implementing.

I cannot tell people what they should take or not take. I can inform people items that have better odds of improving their microbiome as a results on numeric calculations. I am a trained experienced statistician with appropriate degrees and professional memberships. All suggestions should be reviewed by your medical professional before starting.

The answers above describe my logic and thinking and is not intended to give advice to this person or any one. Always review with your knowledgeable medical professional.

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