Today I had a long Zoom call with someone that we hope to cooperate with for Long COVID. She mentioned that one species of probiotics works very well for some people with long COVID and it’s sibling do not. I explained that my working hypothesis is that a lot of interactions depends on the enzymes.

This resulted in us doing a quick lookup experiment using Microbiome Prescription databases.

• Bifidobacterium adolescentis is what worked well. I looked up what enzymes it had, 469
• Then I removed those that are also found in Bifidobacterium animalis subsp. lactis, that left 51 that was only in Bifidobacterium adolescentis
• Removed those also found in Bifidobacterium breve dropping the count to 28
• Removed those also found in Bifidobacterium longum subsp. infantis dropping the count to 17
• Removed those also found in Bifidobacterium longum dropping the count to 15
• Removed those also found in Bifidobacterium bifidum dropping the count to 13 unique enzymes not in the sibling strains.

I kept to only the probiotics that are retail available.

This hints that the reason that it works is due to the following enzymes (linked to Kyoto Encyclopedia of Genes and Genomes):

• sorbose reductase;Sou1p
• coenzyme F420 hydrogenase;8-hydroxy-5-deazaflavin-reducing hydrogenase;F420-reducing hydrogenase;coenzyme F420-dependent hydrogenase
• opine dehydrogenase;(2S)-2-{[1-(R)-carboxyethyl]amino}pentanoate dehydrogenase (NAD+, L-aminopentanoate-forming)
• homocysteine S-methyltransferase;S-adenosylmethionine homocysteine transmethylase;S-methylmethionine homocysteine transmethylase;adenosylmethionine transmethylase;methylmethionine:homocysteine methyltransferase;adenosylmethionine:homocysteine methyltransferase;homocysteine methylase;homocysteine methyltransferase;homocysteine transmethylase;L-homocysteine S-methyltransferase;S-adenosyl-L-methionine:L-homocysteine methyltransferase;S-adenosylmethionine-homocysteine transmethylase;S-adenosylmethionine:homocysteine methyltransferase
• lysyltransferase;L-lysyl-tRNA:phosphatidylglycerol 3-O-lysyltransferase
• cellobiose phosphorylase
• diacylglycerol kinase (ATP);diglyceride kinase (ambiguous);1,2-diacylglycerol kinase (phosphorylating) (ambiguous);1,2-diacylglycerol kinase (ambiguous);sn-1,2-diacylglycerol kinase (ambiguous);DG kinase (ambiguous);DGK (ambiguous);ATP:diacylglycerol phosphotransferase;arachidonoyl-specific diacylglycerol kinase;diacylglycerol:ATP kinase;ATP:1,2-diacylglycerol 3-phosphotransferase;diacylglycerol kinase (ATP dependent)
• beta-glucoside kinase;beta-D-glucoside kinase (phosphorylating)
• sulfur carrier protein ThiS adenylyltransferase;thiF (gene name)
• allantoinase
• 5-oxoprolinase (ATP-hydrolysing);pyroglutamase (ATP-hydrolysing);oxoprolinase;pyroglutamase;5-oxoprolinase;pyroglutamate hydrolase;pyroglutamic hydrolase;L-pyroglutamate hydrolase;5-oxo-L-prolinase;pyroglutamase
• glutamate decarboxylase;L-glutamic acid decarboxylase;L-glutamic decarboxylase;cysteic acid decarboxylase;L-glutamate alpha-decarboxylase;aspartate 1-decarboxylase;aspartic alpha-decarboxylase;L-aspartate-alpha-decarboxylase;gamma-glutamate decarboxylase;L-glutamate 1-carboxy-lyase
• sirohydrochlorin cobaltochelatase;CbiK;CbiX;CbiXS;anaerobic cobalt chelatase;cobaltochelatase [ambiguous];sirohydrochlorin cobalt-lyase

In theory, the 13 items above may be excellent candidates for novel pharmaceuticals to be trialed for treating long COVID.

This same approach may be done with other conditions and probiotics. By trials identify which probiotics have the most impact, use the same approach to identify possible enzymes causing the difference, then do a clinical trial.

This blog is using reports from NirvanaBiome for three members of a family. NirvanaBiome use CosmosID for processing.

In this analysis we have people from the same family, implies DNA and inherited microbiome are similar.

• A 10 y.o. son who has ASD/ADHD.
  • Eats various meats, dairy, grains, some beans, and a limited variety of vegetables and fruit. 
• A 7 y.o. daughter who has been battling constipation for a little over a year now and had some sort of traveler’s diarrhea back in 2017 from which her GI system never seemed to fully recover IMO.
  • She’s a very picky and self-limited eater.  Refuses to eat any meat, but she does consume dairy in the form of yogurt and cheese and ice cream.  Most of her diet is some form of processed carb, and the only fruits and vegetables she consumes are in the form of vegetable powders – potato starch based vegetable chips, granola bars with vegetable powder in them, fruit and vegetable powder added to pancakes, etc.  She will eat fruit pouches that contain peach, apricot and banana, and she will sometimes eat fresh broccoli, cauliflower, some hummus and red lentil pasta..  She will drink a whey protein drink , and mother adds pea protein powder to things like pancakes as well. 
• The mother diet is similar to the son’s diet

Analysis

Before getting to suggestions, I want to use the available information to understand better the three microbiome, especially since two are children. Children have a different microbiome than adults. Caution has to be taken with any data of children — we do not know what “normal” is because studies are rarely age specific.

• Aging progression of human gut microbiota [2019]
• The microbiome: An emerging key player in aging and longevity [2020]
• Unique gut microbiome patterns linked to healthy aging, increased longevity [2021]
• “We show that disease-microbiome associations display specific age-centric trends.” [2020]

I first look at clustering of bacteria, looking at bacteria in common to all three using percentiles. The number of bacteria that had readings very close to each other was shockingly high, far more than I had expected.

Bacteria Name	Rank	Son	Mother	Daughter
Ruminococcus lactaris	species	92.4	93.7	93.5
Oscillibacter ruminantium	species	81.5	83.6	83.3
Alistipes indistinctus	species	79.5	76.8	80.2
Faecalibacterium	genus	25.4	27.9	29
[Bacteroides] coagulans	species	41.4	44.7	41.1
Hungatella	genus	0.2	4	4
Porphyromonadaceae	family	20.4	16.3	20.8
Adlercreutzia equolifaciens	species	95	98	92.8
Bifidobacterium catenulatum	species	95.4	99.2	93.9
Ruminococcaceae bacterium CC59_002D	strain	88.9	94.4	94.4
Aminicella	genus	90.6	85.4	91.2
Salinispirillum marinum	species	34.2	30.9	37.5
Eubacteriaceae	family	61.8	66.2	58.8
CCUG 54292	species	67.3	59.6	67.3
Eubacterium ruminantium	species	57.8	54.4	62.1
Eubacterium	genus	58.9	63.5	55.8
Burkholderiales	order	18.2	25.9	22.2
Fibrobacteria	class	18.3	26.1	22.5
Bifidobacterium pseudocatenulatum	species	87.2	93.8	86
Coprococcus catus GD/7	strain	37.5	33.3	29.2
Sutterellaceae	family	19	16.3	24.7
Clostridium sp.	species	79.4	76.7	85.2

The amount of similarity caused me to want to cross check that this pattern is actually there and not the result of randomness.

Is this “seeing things” in the data or Seeing things?

I grab three other samples from different people who used CosmosId and plotted the difference between bacteria that were share in common. The number of bacteria in common with the family is 2.3x more than a random sample. Remember that many families will be found in almost all samples.

Filtering on species, results in a more dramatic change, with 2.68x more in common. Moving down to strains, it increased further to 3.64x more in common.

The shared diet, living space and DNA clearly results in a “family microbiome” pattern. It would be interesting to do an analysis of some couples that have lived together for at least 10 years (any volunteers?)

We will be using this shared pattern for a customized analysis. It may allow us to better isolated what may be contributing to the two issues cited above (and ignore items that may be high or low compared to the general population)

Identifying Probable Age related items

The microbiome changes with age, and for a number of bacteria we see what appear to be an age based signature.

Given that two are children and one is an adult, we can use how the microbiome changes with age to explain more of the results. The mother is either significantly higher to the levels seen by the kids, or significantly lower.

Bacteria Name	Rank	Son	Mother	Daughter
Rhodocyclaceae	family	0.3	10.8⬆️	3.5
Lactobacillaceae	family	6.4	12.5⬆️	2.4
Fibrobacteres	phylum	5.1	16.3⬆️	7.5
Varibaculum cambriense	species	3.5	16.6⬆️	8.8
Clostridium clostridioforme	species	0	11.3⬆️	3.8
FCB group	clade	8.7	19.2⬆️	4.7
Bacteroidetes/Chlorobi group	clade	8.2	19.1⬆️	4.2
Bacteroidetes	phylum	7.2	18.3⬆️	2.8
Tyzzerella	genus	0.7	17.3⬆️	3
Fusobacterium	genus	3	17.1⬆️	0.5
Bacteroidetes	class	7.3	20.2⬆️	3
Bacteroidales	order	7.3	20.2⬆️	3
Faecalibacterium prausnitzii (Hauduroy et al. 1937) Duncan et al. 2002	species	22	40.1⬆️	21.1
Corynebacteriaceae	family	9.2	21.3⬆️	1.6
Caseobacter	genus	9	21.4⬆️	1.6
Christensenella	genus	69.4	90.3⬆️	68.2
Christensenellaceae	family	66.4	88.9⬆️	65.2
Fibrobacteria	class	18.3	26.1⬆️	22.5
Bacteroides rodentium	species	3.8	28.1⬆️	5.4
Bryantella formatexigens	species	5.4	28.8⬆️	0.7
unclassified Erysipelotrichaceae (miscellaneous)	no rank	28.8	5.8👇	34.6
Lachnospira	genus	3.2	30.3⬆️	1
Parabacteroides distasonis CL09T03C24	strain	70	40👇	70
Ruminococcus gnavus	species	60.8	30.7👇	60.7
Desulfovibrionaceae	family	27.5	58.1⬆️	31.9
Desulfovibrionales	order	27.3	58⬆️	31.8
Phocaeicola	genus	57.6	25.6👇	55.3
Eubacterium hallii	species	58.4	90.5⬆️	69.8
Butyrivibrio	genus	9.2	36.9⬆️	4.2
Intestinimonas	genus	26.3	6.4👇	46.5
Bilophila	genus	31	71.⬆️1	37.5

The kids have two different issues:

• ASD/ADHD
• Constipation

If there was a third normal child in the same age range, picking bacteria would likely be trivial. What we have are just the difference. We do not know if having higher or lower is the cause of the issue. What we do have are bacteria to research and the mother.

Bacteria Name	Rank	Son	Mother	Daughter
Actinobaculum	genus	84.4	29.9	4.5👇
Actinomadura	genus	36.9	26.2	0.1👇
Agathobaculum	genus	0.7	1.4	21.7⬆️
Alistipes	genus	77.4	96.9	35.6👇
Clostridioides	genus	81.3⬆️	24.4	35.6
Coprobacillus	genus	81.3⬆️	4	0.7
Discomyces	genus	4.8👇	93.9	42.5
Dorea	genus	75.3	98.9	20.1👇
Eggerthella	genus	95.8⬆️	46	21.7
Erysipelatoclostridium	genus	0.8👇	9.4	6.1
Escherichia	genus	32.5👇	70.8	61.8
Flavonifractor	genus	0.1👇	15.4	20.4
Holdemania	genus	12.1👇	17.9	21.5
Intestinibacter	genus	26.8	6	58.3⬆️
Lactobacillus	genus	20.4	29.9	11👇
Oscillibacter	genus	44.7	43.5	80.3⬆️
Pseudoflavonifractor	genus	0.3👇	47.7	40.8
Roseburia	genus	4.7	28.7	57.7⬆️
Ruminococcus	genus	3.7👇	95.4	37.9
Streptococcus	genus	83.3⬆️	69.1	2.6
Subdoligranulum	genus	37.2	47.9	74.2⬆️
Veillonella	genus	0.4👇	14.9	9.4

Looking at US Library of Medicine studies on ADHD, we have the following matches for the son:

• Alistipes (NCBI:239759 )
• Eggerthella (NCBI:84111 )
• Ruminococcus (NCBI:1263 )

Looking at Autism

• Alistipes (NCBI:239759 )
• Dorea (NCBI:189330 )
• Escherichia (NCBI:561 )
• Flavonifractor (NCBI:946234 )
• Lactobacillus (NCBI:1578 )
• Roseburia (NCBI:841 )
• Ruminococcus (NCBI:1263 )
• Veillonella (NCBI:29465 )

Nine shifts appear to match studies reported for the son.

Shifting to the daughter for constipation (using Functional constipation / chronic idiopathic constipation), we have just one

• Ruminococcus (NCBI:1263 )

It is important to remember that the studies being referred to, were done on adults usually.

I was curious about Actinomadura because of the differences. It appears to occur in about 3% of samples, hence to get a reasonable sample to get relationships from, a clinical study would need to have 30/3% = 1000 participants and use a 16s processor that detects this bacteria (many do not). Worst yet, because of this rarity, we know of nothing that impacts it.

What to do when there is no information on changing a bacteria!!!

This actually opens the door to using bacteria-to-bacteria associations. We have 111 of them!

Looking at one with the highest positive associations, Desulfofarcimen, we see some items that will increase this bacteria (and by increasing that bacteria, Actinomadura should increase): cranberry polyphenols, Goji (berry,juice), walnuts, saccharin. Using all of the 111 interactions, we found only one thing that shows up as increasing Actinomadura (and many things to decrease), choline deficiency (i.e. reduce choline in diet). Items to avoid would be:

• jatropha curcas linn. (euphorbiaceae)
• nigella sativa seed (black cumin)
• oplopanax horridus(Devil’s Club)
• hypericin(St. John’s Wort)
• kefe cumin (laser trilobum l.)
• foeniculum vulgare (Fennel)
• lactobacillus bulgaricus (probiotics)

The only likely item would be yogurt containing lactobacillus bulgaricus).

Fortunately, most of the bacteria at the genus level has some studies on them.

Symptom Prediction

This is from binary logistic regression which I have been working on but have not released. I picked the symptoms that appear viable for the reported issues. This is problematic because the regression was trained on adult data and not children — this is a mere exploration

The higher the number, the more likely, the lower the number the less likely.

SYmptomName	Son	Mother	Daughter
Neurological: Short-term memory issues	-1.8	-4.0	-2.5
Neurological: Disorientation	-5.1	-7.2	-6.6
Immune Manifestations: Constipation	0.5	-0.2	1.2
Neurological: High degree of Empathy before onset	-5.6	-45.7	-18.4
Comorbid: Small intestinal bacterial overgrowth (SIBO)	-3.4	1.1	-3.9
Asymptomatic: Live in house with person with probable microbiome dysfunction	-7.2	1.5	-11.2
Neurocognitive: Difficulty paying attention for a long period of time	0.7	0.3	-0.3
Neurocognitive: Can only focus on one thing at a time	0.0	-4.5	-3.6
Autism: Official Diagnosis	-1.8	-3.8	-2.5
Comorbid: Constipation and Explosions (not diarrohea)	0.9	– ∞	1.7
Comorbid: Constipation and Diarrohea (not explosions)	-2.4	0.3	-0.5

The son is the most probable for:

• Autism: Official Diagnosis
  • Neurological: Disorientation
• Neurocognitive: Difficulty paying attention for a long period of time (i.e. ADHD)
  • Neurological: Short-term memory issues
  • Neurocognitive: Can only focus on one thing at a time

The daughter is the most probable for:

• Immune Manifestations: Constipation
  • Comorbid: Constipation and Explosions (not diarrohea)

The mother is most probable for:

• Asymptomatic: Live in house with person with probable microbiome dysfunction
• Comorbid: Small intestinal bacterial overgrowth (SIBO)
• Comorbid: Constipation and Diarrohea (not explosions)

While we had regression-training issues, using the “in the same microbiome family” comparison approach, the prediction largely modelled the actual symptoms reported.

Suggestions

For Daughter

The daughter is the most challenging — only one match to PubMed studies that matches for constipation. I went to the sample, and made sure these two symptoms were marked. Then I went to the new feature:

• #1 is o’donnell / flora-balance containing only bacillus laterosporus or brevibacillus laterosporus
• #2 is Prescript-Assist®/SBO Probiotic
• #3 is bacillus subtilis – which is available in many products
• Others high on the list contains bacillus subtilis

Next I flip over to data from Clinical Studies, The most studied was Lactobacillus rhamnosus GG (i.e. Culturelle®), followed by my old favorite Mutaflor (Escherichia coli strain Nissle 1917) which has limited availability Mutaflor (Canada, Australia, Finland, Germany) with Symbioflor-2 being a good alternative. Remember this is based on number of studies, not effectiveness.

Last, Ruminococcus is a bit of a challenge because both high and low values are associated in the literature — given the age, I deem it not safe to pursue changes in isolation.

Looking at the heath analysis, everything looks good except for high Escherichia coli and Bacteroides fragilis. I suspect bad E.Coli is a factor for the constipation which suggests that the strong good E.Coli in Symbioflor-2 (or Mutaflor) would be beneficial. Using the various expert opinions (remember those are for adults!) we see 8,25, 76, 141 and 172 bacteria being selected.

Going over to consensus, we see the following items outstanding (and likely path of least resistance to the daughter):

• pediococcus acidilactic (probiotic)
• bacillus coagulans (probiotics)
• bifidobacterium longum (probiotics)

And the should-avoid including:

• broccoli
• low energy diet/ calorie restriction
• sorghum

Bottom Line for Daughter

I would be inclined to bacillus subtilis alternating every 2 weeks with bacillus coagulans (probiotics) and bifidobacterium longum (probiotics) as the likely easiest to get. If not sufficient progress, then order Symboflor-2 from Germany (site that ships to the world)

For Son

Doing the same pattern, adding symptoms and then doing KEGG computations for probiotics, we end up with a short list (in order): Prescript-Assist®/SBO Probiotic, enviromedica terraflora sbo probiotic, microbiome labs/ megasporebiotic, o’donnell / flora-balance — not a single lactobacillus or bifidobacterium in the list.

We have a reasonable list of bacteria identified above for Autism and ADHD, so I will run two advance suggestions with 15% selection and US Library of Medicine findings. The results were interesting – there was nothing in common with both sets of suggestions. The top items were:

• arabinoxylan oligosaccharides (prebiotic)
• soy
• inulin (prebiotic)
• lactobacillus plantarum (probiotics)
• lactobacillus rhamnosus gg (probiotics) ** this has been used in 3 studies with positive effects (Effect of probiotic supplementation on cognitive function in children and adolescents: a systematic review of randomised trials.)
• barley

Now over to the canned expert suggestions, Using the various expert opinions (remember those are for adults!) we see 7,10, 66, 121 and 225 bacteria being selected. With the following being good suggestions:

• pediococcus acidilactic (probiotic)
• inulin (prebiotic)
• lactobacillus plantarum (probiotics)
• lactobacillus reuteri (probiotics)
• soy
• Pulses
• high fiber diet

The avoid list top items were

• broccoli
• low energy diet/ calorie restriction
• l-taurine

This is very similar to the daughter and likely reflect the commonality of the microbiome.

The Mother

The meals for the kids are likely good suggestions for the entire family. There are not any active issues with the mother and the commonality of bacteria in all of the microbiome will lead to similar diet. I should mention that alcohol appears on the avoid list (not called out for the kids).

REMINDER

All of these are suggestions coming from mathematical models and not clinical experience. Suggestions should be reviewed by a knowledgeable medical professional before starting.

I am a computer scientist and a statistician. I am not licensed to practice medicine, and where I live has strict laws about ‘appearing to practice medicine’. What I can do for readers is to write a public blog (anonymous) from your data and back story as an education post on using the software and the statistics it produces. I cannot consult. The content should be reviewed by a medical professional before implementing.

This is a follow up to my blog post of Dec 30, 2021. Rosacea, Circulation and mild CFS. The person has tried the suggestions, and now we will attempt to see what the consequences are and the next set of suggestions.

Remember, the suggestions are based on mathematical modelling using clinical studies on study populations, so they may work or not work for individuals.

High Level Measures

• Bacteria Reported
  • Prior: 427
  • Latest: 591 (38% increase in taxonomy)
• Health Status
  • Prior: Healthy 1, Unhealthy 8
  • Latest: Healthy 1, Unhealthy 9
• Dr. Jason Hawrelak Recommendations
  • Prior: 99.7% (effectively excellent!)
  • Latest: 75.3%. What left ideal is below, nothing moved to ideal
    • Bacteroidia went up
    • Bacteroides went up
    • Methanobrevibacter went down
    • Roseburia went down
    • Faecalibacterium prausnitzii still not ideal but went up significantly
• Unhealthy Bacteria: here we had a definite improvement, less ones, lower value
  • Ruminococcus] gnavus dropped off list
  • Anaerotruncus colihominis decreased
  • Bacillus decreased
  • Blautia producta decreased
  • Clostridium decreased
  • Collinsella decreased
  • Corynebacterium dropped off list
  • Dorea decreased
  • Eggerthella lenta dropped off list
  • Legionella drop off list
  • Streptococcus australis decreased
  • Streptococcus vestibularis dropped off list
  • Veillonella atypica joined the list

Bacteria Selected using Expert Criteria

Method	Prior	Latest
Use JasonH (15 Criteria)	5	6
Use Medivere (54 Criteria)	5	6
Use Metagenomics (59 Criteria)	5	6
Use Nirvana/CosmosId (36 Criteria)	5	6
Use XenoGene (22 Criteria)	5	6
Standard Lab Ranges (+/- 2 Std Dev)	8	6
Box Plot Whisker	30	27
Kaltoft-Moltrup Normal Ranges	78	84
Percentile in top or bottom 10 %	63	99

My impression is that the microbiome has become more diverse, in one sense, unstable. The increase in the number of bacteria types reported (591) moved it just above the typical count for BiomeSight (578). My personal experience is that this is a good sign, the microbiome is changing, I experienced this spike is variety before my microbiome settled down into a new, healthier normal.

Symptoms Change

“This things has improved:

• Less bloated
• Seborrhoeic dermatitis is gone 
• Better stool
• Better libido“

Using the regression for all symptoms we had regressions for, we had 154 improved out of 209 items, or 74% had improvement in the prediction of symptoms.

Overall: Appears to be Improved

This person was a challenge originally because there was no dominate shifts or “smoking guns”. Being at the 99+% for Dr. Jason Hawrelak recommendations and the same items returned from other expert suggestions (many with more criteria) had no significant change. Supporting improvement: Increase in bacteria types closer to typical; significant decrease in number of Unhealthy Bacteria; improved symptoms; and last, prediction of symptoms had a major improvement.

Next Round of Suggestions

After the above sample, he actually started two more items:

• 10 days with doxycycline
• started to take rosemary “Feels pretty good taking it. ” 

Probiotics

There are many Ways of Choosing Probiotics, I will look at two below:

KEGG AI Computed Probiotics

The differences actually shocked me, a very very dramatic difference. On the current sample I see what is often on ME/CFS patients list appear at the top: miyarisan (jp) / miyarisan with also L. Plantarum Probiotic Powder. This suggests that he is moving towards/through a more typical ME/CFS microbiome. Given that he has issues but everything appeared normal or good, I take this as a good sign – we are exposing the issues.

Prior Sample

Current Sample

CustomProbiotics.com / L. Brevis Probiotic Powder 2 CustomProbiotics.com / L. Rhamnosus Probiotic Powder 2 digestive care 2 Metabolics / Lactobacillus Rhamnosus Powder 2 miyarisan (jp) / miyarisan 2 PureGG 2 spain (es) / bivos 2 spain (es) / kaleidon 2 spain (es) / ns florabiotic instant 2 spain (es) / suerobivos 2 reg’activ / immune & vitality 1.83 CustomProbiotics.com / L. Salivarius Probiotic Powder 1.67

miyarisan (jp) / miyarisan 907 enviromedica terraflora sbo probiotic 828.67 bio-botanical research / proflora4r restorative probiotic 730.25 perfect pass / perfect pass probiotic bacillus spore 730.25 CustomProbiotics.com / L. Plantarum Probiotic Powder 722.2 goodbelly drink 722.2 HLH BIOPHARMA(DE) / LACTOBACT ® LDL-CONTROL 722.2 jarrow formula / ideal bowel support® lp299v® 722.2 Metabolics / Lactobacillus Plantarum Powder 722.2 Prescript-Assist®/SBO Probiotic 694.5 Sun Wave Pharma/Bio Sun Instant 690.92

We also have the option of probiotics based on symptoms (adjusted for the microbiome). See Using Samples and Symptoms to Suggest Probiotics post. The data is shown below in decreasing weight order. The nice thing to see is the decrease in the weight of everyone. One totally disappeared (the sole enterococcus faecalis one). It is interesting to note that while above using only the microbiome and resulted in major shifts between samples, when the symptoms are combined the suggestions are very similar and actually reflect improvement of the microbiome.

Prior Sample	Latest Sample
Prescript-Assist®/SBO Probiotic (34) enviromedica terraflora sbo probiotic (4.4) symbiopharm / symbioflor 1 (3.8) klaire labs / biospora (3.7) microbiome labs/ megasporebiotic (3.6)	Prescript-Assist®/SBO Probiotic (22.6) enviromedica terraflora sbo probiotic (3.5) perfect pass / perfect pass probiotic bacillus spore (2.9) klaire labs / biospora (2.8) microbiome labs/ megasporebiotic (2.7)

Suggestions

I am going to do my current practice of relying on consensus reports because they are now quick to generate. I will be doing a consensus from:

• Standard Lab Ranges (+/- 2 Std Dev)
• Box Plot Whisker
• Kaltoft-Moltrup Normal Ranges
• Percentile in top or bottom 10 %

I will be including everything, since the reader is able to persuade his medical professional to prescribe.

Consensus Results

The following are my picks from the options presented. I provided some links to where it helped ME/CFS –i.e. the suggestions are reasonable

• On all Safest Suggestions (Take:avoid ration)
  • Cacao (21:1) — you likely want 85% chocolate or higher [2010]
  • lactobacillus casei (probiotics) (8:1) [2009]
  • polymannuronic acid (6:1) impacts restless leg syndrome
  • bacillus subtilis (probiotics) (5:1) see 2016 post
  • high fiber diet (5:1)
  • garlic (allium sativum) (5:1)
  • rosmarinus officinalis (rosemary) (3:1)
  • lauric acid(fatty acid in coconut oil,in palm kernel oil,) (7:1)
  • Only take – no negatives
    • fucoidan
    • pediococcus acidilactic (probiotic)
    • green tea
    • capsaicin (hot pepper)
    • fish oil

Items to reduce or avoid

• stevia
• xylan (prebiotic)
• high sugar diet
• sugar
• galactose (milk sugar)
• low fodmap diet
• high-saturated fat diet
• rare meat
• low fiber diet
• high processed foods diet
• vegetable/fruit juice-based diets
• nuts
• white button mushrooms
• partially hydrolysed guar gum,fructo-oligosaccharides (prebiotic)
• cranberry bean flour
• kefir
• kombucha
• Prescript Assist (Original Formula)

Remember: These are suggestions, items that improve odds.

Prescription Suggestions

This is done using advance suggestions and flipping the selections:

The top suggestions were:

• rifaximin (antibiotic)s
• piperacillin-tazobactam (antibiotic)s
• loracarbef (antibiotic)
• benzylpenicillin sodium (antibiotic)
• clindamycin (antibiotic)s
• benzathine benzylpenicillin (antibiotic)
• clarithromycin (antibiotic)s

Secondary positive suggestions are:

• lymecycline (antibiotic)
• minocycline (antibiotic)s
• doxycycline (antibiotic)s

Dangers of Filtering

The person tried using the ME/CFS filter and got very different results. This person has mild ME/CFS; the studies on the US National Library of Medicine are for ME/CFS are typically severe and matches a yard of criteria for inclusion in the study. It is often not safe to use there filters when you self-diagnosis or are mild/controlled.

Bacteria Selected using Expert Criteria

Method	Filtering By ME/CFS	Latest
Use JasonH (15 Criteria)	4	6
Use Medivere (54 Criteria)	4	6
Use Metagenomics (59 Criteria)	4	6
Use Nirvana/CosmosId (36 Criteria)	4	6
Use XenoGene (22 Criteria)	4	6
Standard Lab Ranges (+/- 2 Std Dev)	3	6
Box Plot Whisker	5	27
Kaltoft-Moltrup Normal Ranges	12	84
Percentile in top or bottom 10 %	8	99

My usual criteria has been to have at least 1-2 dozen bacteria. With the new consensus report, having a large number of bacteria seems to produce clearer results.

Bottom Line

Suggestions to be discussed with their medical probiotics

• miyarisan (jp) / miyarisan
• bacillus probiotics (enviromedica terraflora sbo probiotic contains 5 different one)
• L. Plantarum Probiotic

In terms of prescription (doing rotation with breaks between):

• rifaximin (antibiotic)s see this post.
• lymecycline (antibiotic) or minocycline (antibiotic)s There is a long history of successful tetracycline (this family of antibiotics) use with ME/CFS

Supplements to try:

• Monolaurin (lauric acid(fatty acid in coconut oil,in palm kernel oil,)
• Fish Oil – if you love herring… go to it
• High Fiber Diet

We saw improvements between the sample when this reader implemented some of the suggestions. Remember, the suggestions improves the odds, they do not guarantee nor is there any requirement or protocol to follow.

Follow up Comments from the person

Watched the video you uploaded – it was great to get a video and watch how you did for my test.
Quercetin and resveratrol seems to be something to avoid when I did it your way – so I will cut that out.

High red meat and high beef diet seems to be something to avoid (felt it myself also).Been cutting out all red meat for some days now – feels pretty good.
One thing to avoid is also “vegetable/fruit juice-based diets”. I drink like 1-1,5 liter juice a day. I will try to reduce it but it’s really hard – do not feel good eating to much meat, fat or starch. So when cutting out juice I do not get enough calories. Calories are really important to me – which I also see now on my avoid-list – “low energy diet/ calorie restriction” is on it. 
One other thing that is interesting is that potatoes is on the “Highest Adverse Risk”-list. I eat potatoes every day.

I extracted out the items that are recurring as good predictors for various symptoms. These are listed below. This is intended for those interested in research and diving deep. See AI Computed Probiotics from Symptoms for background.

See also Key Enzymes for Symptoms and Key Compounds for Symptoms. What is surprising is that “non-of-the-usual suspects” were included with the exception of spotted fever groups (i.e. Rickettsia, Lyme) and Staphylococcus aureus (see Staphylococcus aureus – the CFS maintainer?)

tax_name	tax_rank	Taxon
Protostomia	clade	33317
Calditrichia	class	1962850
Paraneoptera	cohort	33342
Alteromonadaceae	family	72275
Coxiellaceae	family	118968
Euzebyaceae	family	908622
Holophagaceae	family	574976
Ignavibacteriaceae	family	795749
Nocardiopsaceae	family	83676
Thermoanaerobacterales Family III. Incertae Sedis	family	543371
unclassified Clostridiales	family	186813
Alkalibaculum	genus	696745
Anaerobium	genus	1855714
Anaerocella	genus	1634949
Anaerococcus	genus	165779
Cellulosilyticum	genus	698776
Cryomorpha	genus	246876
Desulfomonile	genus	2357
Euzebya	genus	908623
Haliangium	genus	162027
Hungatella	genus	1649459
Lacibacterium	genus	1500420
Pectobacterium	genus	122277
Spiroplasma	genus	2132
Sporomusa	genus	2375
Terrisporobacter	genus	1505652
Trichococcus	genus	82802
Vagococcus	genus	2737
Neoptera	infraclass	33340
unclassified Chloroflexi	norank	167963
Actinomycetales	order	2037
Chlorobiales	order	191411
Euzebyales	order	908621
Hemiptera	order	7524
Ignavibacteriales	order	795748
Acetonema longum	species	2374
Anaerobranca zavarzinii	species	436000
Anaeromyxobacter dehalogenans	species	161493
Bacteroides propionicifaciens	species	392838
Bifidobacterium thermacidophilum	species	246618
Brevibacterium paucivorans	species	170994
Brochothrix thermosphacta	species	2756
Caloramator mitchellensis	species	908809
Candidatus Tammella caduceiae	species	435141
Carboxylicivirga linearis	species	1628157
Casaltella massiliensis	species	938278
Corynebacterium canis	species	679663
Desemzia incerta	species	82801
Desulfarculus baarsii	species	453230
Desulfonispora thiosulfatigenes	species	83661
Desulfovibrio idahonensis	species	575978
Desulfovibrio psychrotolerans	species	415242
Desulfurispirillum alkaliphilum	species	393030
Dolosigranulum pigrum	species	29394
Haliscomenobacter hydrossis	species	2350
Lactobacillus japonicus	species	29399
Marvinbryantia formatexigens	species	168384
Mediterraneibacter faecis	species	592978
Megasphaera hominis	species	159836
Phascolarctobacterium succinatutens	species	626940
Proteiniborus ethanoligenes	species	415015
Pseudoflavonifractor capillosus	species	106588
Pseudoramibacter alactolyticus	species	113287
Pseudoscillatoria coralii	species	693994
Skermanella aerolata	species	393310
Slackia sp. NATTS	species	647703
Spiroplasma ixodetis	species	2141
Staphylococcus aureus	species	1280
Streptomonospora alba	species	183763
Thermoactinomyces vulgaris	species	2026
Thermophagus xiamenensis	species	385682
Thermovenabulum ferriorganovorum	species	159731
Uliginosibacterium gangwonense	species	392736
Veillonella criceti	species	103891
Verrucomicrobium spinosum	species	2736
spotted fever group	species group	114277
Eukaryota	superkingdom	2759

I extracted out the items that are recurring as predictors for various symptoms. These are listed below. This is intended for those interested in research and diving deep. See AI Computed Probiotics from Symptoms for background

See also: Key Enzymes for Symptoms and Key Compounds for Symptoms

CompoundName	Formula
(S)-Limonene	C10H16
10-Formyltetrahydrofolate	C20H23N7O7
2-Methyl-3-oxopropanoate	C4H6O3
3-Oxo acid	C3H3O3R
4-Hydroxybutanoic acid	C4H8O3
Alcohol	HOR
Amino acid	C2H4NO2R
Ammonia	NH3
CDP-ribitol	C14H25N3O15P2
CoA	C21H36N7O16P3S
D-Amino acid	C2H4NO2R
D-Aspartate	C4H7NO4
D-Galactose	C6H12O6
Ethylamine	C2H7N
Formate	CH2O2
Geranyl diphosphate	C10H20O7P2
Haloacetate	C2H3O2X
L-Homocysteine	C4H9NO2S
L-Idonate	C6H12O7
Mannitol	C6H14O6
Methanol	CH4O
N-Acylneuraminate 9-phosphate	C10H17NO12PR
NAD+	C21H28N7O14P2
NADH	C21H29N7O14P2
NADP+	C21H29N7O17P3
NADPH	C21H30N7O17P3
N-Carbamoylputrescine	C5H13N3O
Orthophosphate	H3PO4
Oxygen	O2
Peptide	C2H4NO2R(C2H2NOR)n
Phosphatidylglycerol	C8H13O10PR2
Pyridoxal	C8H9NO3
Pyruvate	C3H4O3
Thioredoxin disulfide	C10H12N4O4S2R4
Trimethylamine	C3H9N
Trimethylamine N-oxide	C3H9NO
tRNA(Gln)
tRNA(Ile)
tRNA(Pro)
tRNA(Ser)
tRNA(Thr)
tRNA(Trp)
UDP-glucuronate	C15H22N2O18P2

I extracted out the items that are recurring as predictors for various symptoms. These are listed below. This is intended for those interested in research and diving deep. See AI Computed Probiotics from Symptoms for background.

See also: Key Bacteria for Symptoms and Key Compounds for Symptoms

EcKey	OtherName	EnzymeName
1.15.1.1	superoxide dismutase;superoxidase dismutase;copper-zinc superoxide dismutase;Cu-Zn superoxide dismutase;ferrisuperoxide dismutase;superoxide dismutase I;superoxide dismutase II;SOD;Cu,Zn-SOD;Mn-SOD;Fe-SOD;SODF;SODS;SOD-1;SOD-2;SOD-3;SOD-4;hemocuprein;erythrocuprein;cytocuprein;cuprein;hepatocuprein	superoxide:superoxide oxidoreductase
1.17.1.1	CDP-4-dehydro-6-deoxyglucose reductase;CDP-4-keto-6-deoxyglucose reductase;cytidine diphospho-4-keto-6-deoxy-D-glucose reductase;cytidine diphosphate 4-keto-6-deoxy-D-glucose-3-dehydrogenase;CDP-4-keto-deoxy-glucose reductase;CDP-4-keto-6-deoxy-D-glucose-3-dehydrogenase system;NAD(P)H:CDP-4-keto-6-deoxy-D-glucose oxidoreductase	CDP-4-dehydro-3,6-dideoxy-D-glucose:NAD(P)+ 3-oxidoreductase
1.19.1.1	flavodoxin—NADP+ reductase;FPR	flavodoxin:NADP+ oxidoreductase
1.2.1.10	acetaldehyde dehydrogenase (acetylating);aldehyde dehydrogenase (acylating);ADA;acylating acetaldehyde dehyrogenase;DmpF;BphJ	acetaldehyde:NAD+ oxidoreductase (CoA-acetylating)
1.3.1.1	dihydropyrimidine dehydrogenase (NAD+);dihydropyrimidine dehydrogenase;dihydrothymine dehydrogenase;pyrimidine reductase;thymine reductase;uracil reductase;dihydrouracil dehydrogenase (NAD+)	5,6-dihydropyrimidine:NAD+ oxidoreductase
1.4.1.1	alanine dehydrogenase;AlaDH;L-alanine dehydrogenase;NAD+-linked alanine dehydrogenase;alpha-alanine dehydrogenase;NAD+-dependent alanine dehydrogenase;alanine oxidoreductase;NADH-dependent alanine dehydrogenase	L-alanine:NAD+ oxidoreductase (deaminating)
1.7.1.13	preQ1 synthase;YkvM;QueF;preQ0 reductase;preQ0 oxidoreductase;7-cyano-7-deazaguanine reductase;queuine synthase (incorrect as queuine is not the product);queuine:NADP+ oxidoreductase (incorrect as queuine is not the product)	7-aminomethyl-7-carbaguanine:NADP+ oxidoreductase
1.97.1.4	[formate-C-acetyltransferase]-activating enzyme;PFL activase;PFL-glycine:S-adenosyl-L-methionine H transferase (flavodoxin-oxidizing, S-adenosyl-L-methionine-cleaving);formate acetyltransferase activating enzyme;formate acetyltransferase-glycine dihydroflavodoxin:S-adenosyl-L-methionine oxidoreductase (S-adenosyl-L-methionine cleaving);pyruvate formate-lyase activating enzyme;pyruvate formate-lyase 1 activating enzyme	[formate C-acetyltransferase]-glycine dihydroflavodoxin:S-adenosyl-L-methionine oxidoreductase (S-adenosyl-L-methionine cleaving)
2.10.1.1	molybdopterin molybdotransferase;MoeA;Cnx1 (ambiguous)	adenylyl-molybdopterin:molybdate molybdate transferase (AMP-forming)
2.2.1.1	transketolase;glycolaldehydetransferase	sedoheptulose-7-phosphate:D-glyceraldehyde-3-phosphate glycolaldehydetransferase
2.5.1.1	dimethylallyltranstransferase;geranyl-diphosphate synthase;prenyltransferase;dimethylallyltransferase;DMAPP:IPP-dimethylallyltransferase;(2E,6E)-farnesyl diphosphate synthetase;diprenyltransferase;geranyl pyrophosphate synthase;geranyl pyrophosphate synthetase;trans-farnesyl pyrophosphate synthetase;dimethylallyl-diphosphate:isopentenyl-diphosphate dimethylallyltranstransferase	prenyl-diphosphate:3-methylbut-3-en-1-yl-diphosphate prenyltranstransferase
2.6.1.1	aspartate transaminase;glutamic-oxaloacetic transaminase;glutamic-aspartic transaminase;transaminase A;AAT;AspT;2-oxoglutarate-glutamate aminotransferase;aspartate alpha-ketoglutarate transaminase;aspartate aminotransferase;aspartate-2-oxoglutarate transaminase;aspartic acid aminotransferase;aspartic aminotransferase;aspartyl aminotransferase;AST (ambiguous);glutamate-oxalacetate aminotransferase;glutamate-oxalate transaminase;glutamic-aspartic aminotransferase;glutamic-oxalacetic transaminase;glutamic oxalic transaminase;GOT (enzyme) [ambiguous];L-aspartate transaminase;L-aspartate-alpha-ketoglutarate transaminase;L-aspartate-2-ketoglutarate aminotransferase;L-aspartate-2-oxoglutarate aminotransferase;L-aspartate-2-oxoglutarate-transaminase;L-aspartic aminotransferase;oxaloacetate-aspartate aminotransferase;oxaloacetate transferase;aspartate:2-oxoglutarate aminotransferase;glutamate oxaloacetate transaminase	L-aspartate:2-oxoglutarate aminotransferase
2.8.1.1	thiosulfate sulfurtransferase;thiosulfate cyanide transsulfurase;thiosulfate thiotransferase;rhodanese;rhodanase	thiosulfate:cyanide sulfurtransferase
2.9.1.1	L-seryl-tRNASec selenium transferase;L-selenocysteinyl-tRNASel synthase;L-selenocysteinyl-tRNASec synthase selenocysteine synthase;cysteinyl-tRNASec-selenium transferase;cysteinyl-tRNASec-selenium transferase	selenophosphate:L-seryl-tRNASec selenium transferase
3.10.1.1	N-sulfoglucosamine sulfohydrolase;sulfoglucosamine sulfamidase;heparin sulfamidase;2-desoxy-D-glucoside-2-sulphamate sulphohydrolase (sulphamate sulphohydrolase)	N-sulfo-D-glucosamine sulfohydrolase
3.11.1.1	phosphonoacetaldehyde hydrolase;phosphonatase;2-phosphonoacetylaldehyde phosphonohydrolase	2-oxoethylphosphonate phosphonohydrolase
3.2.1.1	alpha-amylase;glycogenase;alpha amylase;endoamylase;Taka-amylase A;1,4-alpha-D-glucan glucanohydrolase	4-alpha-D-glucan glucanohydrolase
3.3.1.1	adenosylhomocysteinase;S-adenosylhomocysteine synthase;S-adenosylhomocysteine hydrolase (ambiguous);adenosylhomocysteine hydrolase;S-adenosylhomocysteinase;SAHase;AdoHcyase	S-adenosyl-L-homocysteine hydrolase
3.4.11.1	leucyl aminopeptidase;leucine aminopeptidase;leucyl peptidase;peptidase S;cytosol aminopeptidase;cathepsin III;L-leucine aminopeptidase;leucinaminopeptidase;leucinamide aminopeptidase;FTBL proteins;proteinates FTBL;aminopeptidase II;aminopeptidase III;aminopeptidase I	NULL
3.6.1.1	inorganic diphosphatase	diphosphate phosphohydrolase
3.7.1.12	cobalt-precorrin 5A hydrolase;CbiG	cobalt-precorrin 5A acylhydrolase
3.8.1.2	(S)-2-haloacid dehalogenase;2-haloacid dehalogenase[ambiguous];2-haloacid halidohydrolase [ambiguous][ambiguous];2-haloalkanoic acid dehalogenase;2-haloalkanoid acid halidohydrolase;2-halocarboxylic acid dehalogenase II;DL-2-haloacid dehalogenase[ambiguous];L-2-haloacid dehalogenase;L-DEX	(S)-2-haloacid halidohydrolase
4.4.1.1	cystathionine gamma-lyase;homoserine deaminase;homoserine dehydratase;cystine desulfhydrase;cysteine desulfhydrase;gamma-cystathionase;cystathionase;homoserine deaminase-cystathionase;gamma-CTL;cystalysin;cysteine lyase;L-cystathionine cysteine-lyase (deaminating);CGL	L-cystathionine cysteine-lyase (deaminating; 2-oxobutanoate-forming)
4.6.1.1	adenylate cyclase;adenylylcyclase;adenyl cyclase;3′,5′-cyclic AMP synthetase;ATP diphosphate-lyase (cyclizing)	ATP diphosphate-lyase (cyclizing; 3′,5′-cyclic-AMP-forming)
4.7.1.1	alpha-D-ribose 1-methylphosphonate 5-phosphate C-P-lyase;phnJ (gene name)	alpha-D-ribose-1-methylphosphonate-5-phosphate C-P-lyase (methane-forming)
4.99.1.12	pyridinium-3,5-bisthiocarboxylic acid mononucleotide nickel chelatase;LarC;P2TMN nickel chelatase	Ni(II)-pyridinium-3,5-bisthiocarboxylate mononucleotide nickel-lyase (pyridinium-3,5-bisthiocarboxylate-mononucleotide-forming)
5.1.1.1	alanine racemase;L-alanine racemase	alanine racemase
5.6.1.9	(R)-2-hydroxyacyl-CoA dehydratase activating ATPase;archerase;(R)-2-hydroxyacyl-CoA dehydratase activator;(R)-2-hydroxyacyl-CoA dehydratase activase;fldI (gene name);hgdC (gene name);hadI (gene name);lcdC (gene name)	reduced flavodoxin:(R)-2-hydroxyacyl-CoA dehydratase electron transferase (ATP-hydrolyzing)
6.1.1.1	tyrosine—tRNA ligase	L-tyrosine:tRNATyr ligase (AMP-forming)
6.2.1.1	acetate—CoA ligase;acetyl-CoA synthetase;acetyl activating enzyme;acetate thiokinase;acyl-activating enzyme;acetyl coenzyme A synthetase;acetic thiokinase;acetyl CoA ligase;acetyl CoA synthase;acetyl-coenzyme A synthase;short chain fatty acyl-CoA synthetase;short-chain acyl-coenzyme A synthetase;ACS	acetate:CoA ligase (AMP-forming)
6.3.1.1	aspartate—ammonia ligase;asparagine synthetase;L-asparagine synthetase	L-aspartate:ammonia ligase (AMP-forming)
6.4.1.1	pyruvate carboxylase;pyruvic carboxylase	pyruvate:carbon-dioxide ligase (ADP-forming)
6.5.1.1	DNA ligase (ATP);polydeoxyribonucleotide synthase (ATP);polynucleotide ligase (ambiguous);sealase;DNA repair enzyme (ambiguous);DNA joinase (ambiguous);DNA ligase (ambiguous);deoxyribonucleic ligase (ambiguous);deoxyribonucleate ligase (ambiguous);DNA-joining enzyme (ambiguous);deoxyribonucleic-joining enzyme (ambiguous);deoxyribonucleic acid-joining enzyme (ambiguous);deoxyribonucleic repair enzyme (ambiguous);deoxyribonucleic joinase (ambiguous);deoxyribonucleic acid ligase (ambiguous);deoxyribonucleic acid joinase (ambiguous);deoxyribonucleic acid repair enzyme (ambiguous);poly(deoxyribonucleotide):poly(deoxyribonucleotide) ligase (AMP-forming)	poly(deoxyribonucleotide)-3′-hydroxyl:5′-phospho-poly(deoxyribonucleotide) ligase (ATP)
6.6.1.1	magnesium chelatase;protoporphyrin IX magnesium-chelatase;protoporphyrin IX Mg-chelatase;magnesium-protoporphyrin IX chelatase;magnesium-protoporphyrin chelatase;magnesium-chelatase;Mg-chelatase;Mg-protoporphyrin IX magnesio-lyase	Mg-protoporphyrin IX magnesium-lyase
7.1.1.1	proton-translocating NAD(P)+ transhydrogenase;pntA (gene name);pntB (gene name);NNT (gene name)	NADPH:NAD+ oxidoreductase (H+-transporting)
7.2.1.1	NADH:ubiquinone reductase (Na+-transporting);Na+-translocating NADH-quinone reductase;Na+-NQR	NADH:ubiquinone oxidoreductase (Na+-translocating)
7.3.2.1	ABC-type phosphate transporter;phosphate ABC transporter;phosphate-transporting ATPase (ambiguous)	ATP phosphohydrolase (ABC-type, phosphate-importing)
7.4.2.1	ABC-type polar-amino-acid transporter;histidine permease;polar-amino-acid-transporting ATPase	ATP phosphohydrolase (ABC-type, polar-amino-acid-importing)
7.6.2.10	ABC-type glycerol 3-phosphate transporter;glycerol-3-phosphate ABC transporter;glycerol-3-phosphate-transporting ATPase	ATP phosphohydrolase (ABC-type, sn-glycerol 3-phosphate-importing)

In this post, AI Computed Probiotics from Symptoms, we could calculate probiotics that could help for one symptom at a time for the general population. This is nice if you have just one symptoms and no microbiome details. See Ways of Choosing Probiotics for an overview on picking probiotics.

We can do better, a new page is up that will allow us to calculate the probiotics based on multiple symptoms PLUS your microbiome sample! In other words using all available information. (I will not create a page to handle multiple symptoms with no sample — you need to get a sample).

You must have entered symptoms for this to work. If not, you will see this appearing

After you enter symptoms, a page may appear like below

I should emphasis a few things:

• This is by retail probiotic name.
  • The probiotic must be available somewhere in the world. It may not be available where you live
  • If you wish to know which species are in the probiotic, just click the name.
    • Probiotics with the same numbers are likely the same species (i.e. no difference)
• The Weight is an estimate of how much of the missing enzyme it will provide (weight is based on odds)
• Enzyme Means is the number of Enzymes that will be provided by it
• Species is the number of different species in it.

Practical Example

Using the above example, the person founds that Prescript-Assist®/SBO Probiotic is either not available or too expensive (watch costs!) and proceeded down the list:

• miyarisan (jp) / miyarisan is available by a Japanese website at a reasonable price.
  • Record the species, in this case: clostridium butyricum miyairi
• The next 4 are all the same species, lactobacillus plantarum, the best buy for this person was CustomProbiotics.com / L. Plantarum Probiotic Powder (remember prices vary greatly from place to place)
• Next, they work down the list to find something that contains neither of the above (different strains, different enzymes)… the winning bacteria is: lactobacillus salivarius
• Moving on, we find ImmuneBiotech Medical Sweden AB / GutMagnific® contains 2 of the above, so we skip it… the next one is lactobacillus rhamnosus (37.8) found in 8 different products.

Cross Validation

We have other ways of suggesting probiotics

• Looking them up by research from this page [Search for probiotics by studies] – unfortunately, this will not giving a ranking
• Using the KEGG based calculation without using symptoms:
  

• The third way is by suggestions — here, the choice of bacteria selection can result in a wide variation of probiotics suggested and contradictory results as shown below:

What to do with contrary results?

We potentially have 4 opinions

• From Symptoms + KEGG
• From KEGG alone
• From the literature
• From suggestions

To take or not to take should be done on consensus (i.e. ideally 3 says to take). Of the above methods, the one with the weakest quality of data is from suggestions (because it is so dependent on studies being done! ). For the one in conflict, lactobacillus salivarius (AKA Ligilactobacillus salivarius), there were studies found in the above link (strain specific for retail probiotics), NOTE: I missed them on the first pass because I did not enter the name in “Search for” and had left the default ‘constipation’ there

One of the symptoms was brain fog and depression. “sad mood” is a sufficient match.

To translate the methods into human “detective” terms

• KEGG — DNA is a match
• KEGG + microbiome Sample — DNA and video is a match
• Researched Studies — Profiling by race, sex, age etc is a match (studies are done on populations, not individuals) – it is truly “bacteria profiling”
• Suggestions based on bacteria picked — close to setting up police stops to detect drunk drivers. The number of people arrested depends on time, location etc of where the stops are done.
  

Reminder:

I am a computer scientist and a statistician. I am not licensed to practice medicine, and where I live has strict laws about ‘appearing to practice medicine’. What I can do for readers is to write a public blog (anonymous) from your data and back story as an education post on using the software and the statistics it produces. I cannot consult. The content should be reviewed by a medical professional before implementing.

Back Story

35yr old, female with ME of around 15 years, Coeliac and Crohn’s diagnosed in 2014 plus simple temporal lobe seizures and endometriosis.

I have tested extremely extensively and most labs are generally normal with the exception of:

• Prolactin- always slightly above high end of range
• Lyme ELISA IgM positive but Blot negative (possibly cross-reactive with RF)
• Rheumatoid factor – one point over upper range
• LDH – consistently slightly above range
• Aldolase – tested once, slightly above range
• ALT – occasionally slightly above range
• EBV – positive for past infection but never any evidence of reactivation
• SIBO breath test positive for hydrogen only

I am really struggling with acne… I have been offered Lymecycline for the acne but don’t know if it’s worth the risk. I am currently on a 7-day course of Co-amoxiclav (amoxicillin + clavulanic acid) for an infected cyst (my Biome sample was taken before this).

I was able to control my crohn’s with an elemental diet, followed by strict paleo, then gradually reverting to a more relaxed diet. I did a course of oregano oil which was very harsh on the gut but it got rid of my constant bloating for the first time in my life (this came back and remains since reintroducing carbs). I’m 99.9% sure I’m on the autism spectrum. Interestingly, some of my autistic traits and my ME symptoms abate somewhat for a short period at the beginning of a cold virus (the first couple of days while fever is present). I had a similar temporary reaction to Sulforaphane.

My ME started while I was working full time, following glandular fever in 2006. The onset was characterised by ‘tired but wired’ and rolling PEM, finding it almost impossible to fall asleep until it was nearly time to get up and a complete inability to get into deep sleep. I reduced my working hours gradually but eventually gave up work fully in 2008. Even when ‘healthy’ I never had normal stamina, muscle mass and was really ready for bed by the end of the work day.

Possibly coinciding with my gastrointestinal diagnoses and subsequent avoidance of gluten, my symptoms calmed a bit from the ‘acute’ years, and I began to sleep a little better and get brief symptom-free interludes while at rest. Now, prolonged activity above baseline will lead to a return of the PEM and ‘tired but wired’ symptoms (inability to switch off nonsensical chattering thoughts at night leading to insomnia, feeling hot with chills, feverish, sweats, tossing and turning all night. These symptoms stop on rising but leave me extremely brain fogged from the sleep deprivation, and then repeat the next night. I also experience myalgia, headaches, orthostatic intolerance and strong need to lay horizontal throughout the day. I wake with heavy puffy face and eyelids most days. I go through periods of extreme dry mouth, worse on waking despite always hydrating well.

Even in my symptom-free-at-rest periods, I still struggle to get to sleep some nights, although I keep a strict routine 10pm-10am. I find it very difficult to get into the deeper stages of sleep almost all of the time. Even with all reasonable interventions and ear plugs I am easily startled awake by household sounds and there is usually activity from others from 4-5am onwards.

Microbiome Analysis

I am going to do three levels of Analysis. I will start with generic, then move on to diagnosis using US National Library of Medicine studies and ending with the latest refactor, using bacteria associated with symptoms discovered from uploads to this site.
The purpose of these analysis to get suggestions for the most probable bacteria causing issues.

Overall Health

I will not go step by step (see this post with video for how to do this) but do the following suggestion generation and then look at the consensus

• Jason H – 10 bacteria picked
• Standard Lab Ranges (+/- 2 Std Dev) – 7 bacteria picked
• Box Plot Whisker – 61 bacteria picked
• Kaltoft-Moltrup Normal Ranges – 98 bacteria
• Top Bottom at 5%: 41 bacteria

Then I went to Advance Suggestion with Percentile: 15% and the following PubMed conditions (Remember that Display Level must be Intermediate or higher to see this option):

• Acne – 3 bacteria
• Crohn’s Disease – 24 bacteria
• Celiac Disease – 14 bacteria
• Chronic Fatigue Syndrome – 13 bacteria

Then I went to Symptom Associated to Bacteria (Citizen Science) and found the following applicable items:

• Official Diagnosis: Chronic Fatigue Syndrome (CFS/ME) – 10 bacteria
• Autism – 1 bacteria
• Insomnia – 9 bacteria
• Brain Fog –

For Official Diagnosis: Chronic Fatigue Syndrome (CFS/ME), most of the matched were at the Genus Level

The result is 40 bacteria added to our hand picked list.

Consensus Highlights

We have a lot of different suggestions over our 10 analysis, often more than 1000!

Suggestions to discuss with your medical professional

• lauric acid(fatty acid in coconut oil,in palm kernel oil,) aka Monolaurin – 10 recommends
• whole-grain barley, barley,oat
• apple (as a personal note, my wife has Crohn’s and Pink Lady Apples work best for her)
• Cacao – there are studies with ME/CFS that is effective, 85% or higher is suggested
• bifidobacterium longum (probiotics)
• chondrus crispus (red sea weed)
• lactobacillus paracasei (probiotics)

On the avoid list:

• folic acid,(supplement Vitamin B9) – often I see that B-Vitamins are split between take and avoid, this suggests that B-Complex capsules may not be the best choice.
• high red meat
• low-fat diets
• quercetin,resveratrol
• saccharin
• cannabinoids

Also listed was gluten-free diet. I suspect the type of gluten may be significant.

KEGG Probiotics:

The usual one for ME/CFS are at the top (and were also listed in Safer or Safest Takes) :

• miyarisan (jp) / miyarisan aka clostridium butyricum (probiotics)
• lactobacillus plantarum (probiotics) – available in many products

For supplements:

• beta-alanine – Percentile: 9.7
• D-Ribose – Percentile: 4
• Glycine – Percentile: 13.6
• L-Cysteine – Percentile: 13.6
• L-Threonine – Percentile: 6.5
• Magnesium – Percentile: 0.1

Both D-Ribose and Magnesium are well studied supplements in a ME/CFS context (confirming predictions to clinical practice the items are linked to CFSRemission Blog).

Bottom Line

At this point I will stop for several reasons:

• Purpose was to show the method
• Person has brain fog often, so more notes may be counter productive
• ME/CFS usually have restricted funds, so keeping the number of items low reduces frustrations over not being able to acquire.

A video will be added in the next few days

Questions And Answers

Q: I forgot to mention it, but I do have allergic rhinitis and high cholesterol (as listed under the detected conditions) so this is very accurate.

A: Although I see this often, it keeps surprising me about the accuracy of predictions!

Q: Interesting that it doesn’t pick up on any CFS-related bacteria at a species level, I wonder if this fluctuates and could possibly be because I was relatively low-symptom at the time of the sample, i.e. not in a PEM flare? 

A: You are very likely correct, it does fluctuates. Also, keep in mind that there are many subsets of ME/CFS, so this can be a little hit-and-miss.

Should I take Lymecycline?

A: This is a little complex, we have mixed results.

But when I tried a different antibiotic often prescribed for acne, it is all positive

I would suggest making a counter proposal to your medical professional of minocycline instead.

Q: I’d be interested in your opinion on IgY hyperimmune egg powder supplements for targeting gut pathogens

A: There are many retail products like this. What I found are some vet studies[36 listed here]. I found a list of clinical studies here. My general impression is that it is favorable. There is one word of caution, it appears similar to transfer factor — i.e. the IgY may be targeted to specific bacteria/infections only. Hence, my advice would be to buy just one unit of it, if no response, change to a different brand when you finish it. Remember my motto: Rotate, rotate, rotate….

• Protection Efficacy of Multivalent Egg Yolk Immunoglobulin against Eimeria tenella Infection in Chickens [2013] ” Chickens fed IgY resulted in reduced mortality, increased body weight gain (BWG), reduced oocyst shedding, reduced caecal lesion score and increased anti-coccidial index.”
  • “Oral immunotherapy using egg yolk polyclonal IgYs against Eimeria sp. represents an effective and natural resource against severe E. tenella infection favoring the gradual withdrawal of the anticoccidial drugs and antibiotics.” [2021]
• Impact of Dietary Egg Yolk IgY Powder on Behavior, Meat Quality, Physiology, and Intestinal Escherichia coli Colonization of Broiler Chicks [2022] “Our study concluded that dietary supplementation of 3,000 and/or 4,000 μg/ml IgY improved the growth rates, behavioral activities, intestinal health indices, and meat quality of broiler chicks.”
• Passive Immunization of Chickens with Anti-Enterobactin Egg Yolk Powder for Campylobacter Control [2021] “Collectively, oral administration of broiler chickens with the anti-Ent egg yolk powder failed to confer protection against intestinal colonization of C. jejuni,”

Reminder:

I am a computer scientist and a statistician. I am not licensed to practice medicine, and where I live has strict laws about ‘appearing to practice medicine’. What I can do for readers is to write a public blog (anonymous) from your data and back story as an education post on using the software and the statistics it produces. I cannot consult. The content should be reviewed by a medical professional before implementing.

Back Story

• Male, 57, very high pain tolerance, little tolerance of irritation (itch, slivers, paper cuts, cold, drafts)
  • Diagnosed with Fibromyalgia at age 35
  • Proposed diagnosis of Psoriatic Arthritis last year
• Psoriasis (or eczema since 10 yrs old). Usually cold hands and feet.
• Depression most of my life. 
  • Currently abated by Bupropion, past included: Serzone, Gabapentin,Lyrica
• Always loose bowel movements, but not diarrhea.  Never constipated.
• Musculoskeletal pain all my life. Not worse with activity.
• Restless leg syndrome while sitting,  Had to shift every thirty seconds. 
  • Took pamiprexole for 4 mos.  Stopped PPX, restless leg never returned.
• Felt sick with Aspartame. (Phenylalanine)
• About 20 years ago, with the intention of it being an elimination diet, lived on nothing but boiled eggs and (Chinese dish) Beef & Broccoli (with GF soy sauce, sesame oil, garlic, ginger and olive oil). Swallowed Tbsp of turmeric daily.
  • After 7 months, complete remission.
  • Lapsed diet, Remission lasted 4 mos.  Woke up one morning fully sick. 
• Went on a gluten free, seed free, seed oil free, ketogenic diet about 10 years ago. I suspect the lack of carbs starved a Candida problem.  Much reduced symptoms for about 8 years, downhill slide the last two.
• Taken arthritis-related herbs the last year.  Researching each, (about a hundred researched, perhaps 15 taken) they all seem to benefit the microbiome.
• My kidney and liver labs are very good. My heart scan showed zero plaque deposits.
• Life is pretty miserable.

Note on Fibromyalgia: Bacteria Associated from PubMed, Bacteria Associated from Citizen Science. The only bacteria in common with these two lists is: Hungatella hathewayi. IMHO, Fibromyalgia (as a diagnosis) by itself does not have a strong relationship to the microbiome. There may be strong associations of symptoms to the microbiome.

Microbiome Analysis

I am going to do three levels of Analysis. I will start with generic, then move on to diagnosis using US National Library of Medicine studies and ending with the latest refactor, using bacteria associated with symptoms discovered from uploads to this site.
The purpose of these analysis to get suggestions for the most probable bacteria causing issues

Generic Analysis – Pass #1

This is the suggested path for a first time user to take. We are not targeting for specific issues, rather trying to improve the microbiome towards a typical microbiome. For many people that is sufficient

With the large number of medical issues described above I started by looking at potential medical conditions using National Library of Medicine data. One of the challenges is that the microbiome profiles are often based on naïve patients (i.e. not being treated for anything), he is being treated.

Going further down the page, we see that your microbiome does not have major dysfunction by Dr. Hawrelak criteria (89%ile)

Jumping directly to suggestions

It was interesting that KEGG AI Computed probiotics was very similar to those from a sample that I did a video on [ miyarisan (jp) / miyarisan, enviromedica terraflora sbo probiotic, CustomProbiotics.com / L. Plantarum Probiotic Powder, symbiopharm / symbioflor 1]. For supplements, only L-Threonine – was suggested at a Percentile of 6.8%ile.

Expert Criteria with Consensus

I proceeded to the Expert Criteria page and did each option. I then use the consensus report to identify the best candidates.

The first ones (Use…) all just picked 8 bacteria. Standard Lab Ranges picked 12 bacteria, Box Plot: 55, Kaltoft-Moltrup : 73 and Top/Bottom at 10%: 70. As a reminder, the consensus button appears after doing two suggestions sets in 24 hours. An alternative (since the first 5 picked the same bacteria) is to do just one of the “Use” and each of the others, then look at the consensus (left as an exercise to the reader).

The consensus report key suggestions were:

• Safest Takes
  • inulin (prebiotic) – already taking!
  • barley
  • triphala <– This is one of my favorite to do 2 week pulses on
  • saccharomyces cerevisiae (probiotics)
  • quercetin
• Safer Take
  • Human milk oligosaccharides (prebiotic, Holigos, Stachyose)
  • resistant starch
  • lactobacillus plantarum (probiotics) – On KEGG probiotic list!
  • bacillus subtilis (probiotics) – On KEGG probiotic list!
• Likely Safe Take
  • saccharin
  • glycyrrhizic acid (licorice)
  • Slippery Elm
  • vitamin b3 (niacin)

I noted that some of his past diet types are on the Adverse Risk list, i.e. those choices may have contributed to where he is now (not immediate, but keeping to them long term).

National Library of Medicine Conditions – Pass #2

For this pass, we clear our consensus suggestion. We want the suggestions to be specific.

Since this person has been taking a variety of prescription drugs, I am including that in suggestions. The main reason is to see if there are alternative prescriptions possible that may be more microbiome beneficial. For ME/CFS, often the top items with this choice have been antibiotics that have been used successfully for treating ME/CFS (despite the AI not having that information).

First, we need to determine the conditions that we have data available for and that this reader has. I extracted these as candidates:

• Depression 📚 – resulted in 16 bacteria picked, only one prescription drug,  etoposide a cancer drug
• Psoriasis 📚 – resulted in 9 bacteria picked
• Fibromyalgia 📚 – resulted in 4 bacteria picked
• Arthritis does not have a precise match on the reference page, so I will skip it.

I picked the settings below for the first one. I checked ALL types of Bacteria Modifiers.

For each condition, I just change the last select box.

• Safest Takes
  • barley
  • arabinoxylan oligosaccharides (prebiotic)
  • streptomycin (antibiotic)s
  • lactobacillus reuteri (probiotics)
  • clostridium butyricum (probiotics)
  • butoconazole nitrate,(prescription) – an antifungal
  • clemizole hydrochloride,(prescription) – an antihistamine
  • clofazimine (antibiotic)
• Safer Takes
  • vitamin b3 (niacin)
  • inulin (prebiotic)
  • paromomycin (antibiotic)s
  • Vitamin C (ascorbic acid)
  • iron
• Likely Save Takes
  • quercetin followed by a long list of prescription drugs

I will skip the avoid list, they should be reviewed by the reader. What is interesting to note was that both antihistamine and antifungal drugs showed up based on the bacteria patterns. This suggests that those two issues may warrant investigation.

P.S. I picked 15% arbitrarily, I like to shoot for an average of 6-10 bacteria per set of suggestions being selected to keep the suggestions focused. You may wish to increase or decrease to tune the number selected.

Using Symptoms – Pass #3

This comes out of this weeks refactor. A video of this feature is below (TO DO).

Again, clear the consensus as we did above. Why, because we will likely be running several list of suggestions.

On the resulting page, you will see checkboxes to pick the bacteria that are likely good candidates to change. I went and checked all of them and then clicked the [Add to Hand Pick Selection] button at the top.

I then checked Fibromyalgia and had no luck (we have a small number of people with this condition, so detection is poor).

I then went on to pain, as shown below, and picked General: Myalgia (pain)

We now have a different list of bacteria

At this point, I notice that a Hand Picked Bacteria button appears on my samples page

We then pick the suggestions link on the same drop down. Again pick all modifiers.

For retail probiotics, we have long list with most having similar benefit

Personally, I would likely drop these into rotation (there are no bacteria common to any of them):

• wakamoto (jp) / wakamoto pharmaceutical intestinal drug
•  customprobiotics.com / B. Bifidum Probiotic Powder
•  shin biofermin (jp) /s
•  optibac / saccharomyces boulardii

Bottom Line

Above we saw three different approaches to obtaining suggestions. There was agreement between each of the approaches for over 70% of the items. My usual suggestion to discuss with your MD before starting:

• Take 2 of the following probiotics for two weeks and then rotate to a different pair
  • wakamoto (jp) / wakamoto pharmaceutical intestinal drug
  •  customprobiotics.com / B. Bifidum Probiotic Powder
  •  shin biofermin (jp) /s or symbiopharm / symbioflor 1 (both are the same species)
  •  optibac / saccharomyces boulardii
  • miyarisan (jp) / miyarisan,
  • enviromedica terraflora sbo probiotic,
  • CustomProbiotics.com / L. Plantarum Probiotic Powder
• For foods and supplements
  • Niacin keeps appearing as a to take
  • Do NOT take a B-Complex, several of the B Vitamins are counterindicated
  • Barley (suggest for porridge on most days)
  • Inulin
  • For diet type — the reader needs to do a little work to decide what to do. Some of what he has tried are on the avoid list!

Someone mentions that to me. My initial response is simple… don’t jump to conclusions without supporting lab results. Without lab results, you may feel the same from any of many condition that produces hypoxia (low oxygen delivery). Hyper-coagulation is one possible cause there are others. This is a quick list of items to get objective measures from..

• First, get and monitor your saturated oxygen level. A lot of people have the Fingertip Pulse Oximeters. They are cheap and often under $20. With COVID persisting, they should be in every home first aid kit!
  • Both my wife and I wear a watch that records Saturated O2 every 15 minutes and we can view our history on our phone. See this post.
    

• If you are low, then there can be several possible causes (I will use some automotive analogy):
  • Low iron / problems absorbing iron i.e. Low Hemoglobin – low grade of gas
  • Vascular constriction: the flow of blood is down, so less oxygen gets there, see Peripheral vasoconstriction influences thenar oxygen saturation as measured by near-infrared spectroscopy [2012] – your gas line is pinched….
  • Fibrin deposits slowing blood flow. See The association of oxygen saturation, tomography findings and D-dimer levels in coronavirus disease 2019 patients [2020] – in this the blood is not thick, but “your oil filter is dirty”
  • Your blood may be sticky – the term is often used with Hughes Syndrome or antiphospholipid antibody syndrome (APS),
  • Your blood may be odd shaped. The most extreme case is sickle cell anemia, but studies with ME/CFS patients have a different form, “So it has been proposed – first at the Cambridge Symposium on ME in 1990 and in another article in 1998, that ME is a dysfunctional state resulting from reduced rates of capillary blood flow due to the presence of shape-changed, poorly-deformable red cells” [source] – From Dr. Les Simpson in New Zealand
  • You may have a low red blood cell count. Red blood cells are what carries oxygen
  • You may have a low blood volume “In contrast, ME patients have a volume that can be as low as 50% of normal.” from an 2015 update by Dr. Bell
  • Small heart size — as you age, it is less able to push blood thru as well. “A considerable number of CFS patients have a small heart. Small heart syndrome may contribute to the development of CFS as a constitutional factor predisposing to fatigue, and may be included in the genesis of CFS.” [2008]
  • Also, low blood pressure can come in.
  • If it is truly hypercoagulation — there are tests for that (I personally did them) see Hemex’s ISAC Panel for ME/CFS is available. Be warned, that the standard tests do not cover all types of coagulation issues, also, unless the values are truly extreme — most specialists will ignore the results. See Hypercoagulable states: an algorithmic approach to laboratory testing and update on monitoring of direct oral anticoagulants [2014]

Bottom line: Get lab results when possible and do not speculate. I recall that some supplements will improve certain types of hypercoagulation and make other types worse. Act from objective knowledge and not speculation.