Same old, same old — Microbiome will stay Stuck!

For items like antibiotics and probiotics, I have for a long time been a strong advocated for continuous rotation. The original source for this attitude was Cecil Jadin’s treatment protocol for occult rickettsia (which originated with the Pasteur Institute for Tropical Medicine). This was followed by reading studies finding that rotating or even just pulsing (2 weeks on/ 2 weeks off) was more effective in reducing bacteria than continuous. Probiotics often function via the natural antibiotics they produce (a lot of prescription antibiotics originated with bacteria); hence probiotic rotation became part of my preaching.

If you have microbiome related issues, my soapbox has been “your goal is make the stable dysfunctional microbiome, unstable. Today I read a study on Nature that further clarifies what may be needed.

Together, these findings suggest that the human gut microbiome’s metabolic potential reflects dietary exposures over preceding days and changes within hours of exposure to a novel nutrient. The dynamics of this ecological memory also highlight the potential for intra-individual microbiome variation to affect the design and interpretation of interventions involving the gut microbiome.

Ecological memory of prior nutrient exposure in the human gut microbiome [2022]

If the goal is to make the microbiome unstable, then this gives some clear indication of strategy.

  • Every two weeks change the dominant starch – for example, if pasta is a regular meal item then
    • Made from glucomannan—a starch found in the konjac yam/ Konjac Flour (Source)
    • Made from red lentils and quinoa (Source)
    • Made from white rice flour, organic amaranth flour (Source)
    • Made from chickpea flour, organic yellow lentil flour, organic red lentil flour, organic kale powder, organic spinach powder (source)
  • Every two weeks change dominant proteins source
    • Fish
    • Pork
    • Lamb
    • Duck
    • Chicken
    • Turkey
  • Change vegetables and fruit too…
  • Change main spices used….

The key aspect is that every new addition results in a change of the microbiome. If you have microbiome issues, that is what you want to do. You do NOT want to take the same supplements, herbs, spices, vitamin or comfort food – continuously. You want to shake things up!

Approaching Small intestinal bacterial overgrowth (SIBO) from “the other end”

While the location of SIBO and the results of a stool test are a good physical distance apart, as part of an ongoing series of posts on special studies, I ran SIBO thru this morning — really expecting to find nothing, or perhaps a few overgrowths. To my surprise, the results was significant undergrowth with high statistical significance!

A formal post on the results is in the queue, but I thought that I should make the results available for those who wish to commit SIBO heresy!

On the [Changing Microbiome] tab

SIBO reaches our threshold for inclusion as defined in A new specialized selection of suggestions links. A summary table of various studies has been added there which shows the statistical association is actually pretty strong.

Of course, you are saying “but this is down stream how can it impact upstream?!!?” To me, it is like saying, “I was waiting in a queue and everyone is healthy except the first person in the queue who had COVID, how could I get it?” Bacteria spread, including upstream.

 I should point out that these bacteria may not be the cause, rather they may be ‘the canaries in the coal mine’ of the microbiome.  A few items of special interest are:

BacteriaReference MeanStudy
Shuttleworthia (genus)27333
Prevotella stercorea (species)637831
Coprococcus eutactus (species)79871463
Streptococcaceae (family)35671473
Veillonellaceae (family)1729510944
Tissierellales (order)41621457
Peptoniphilaceae (family)41581456

In terms of enzymes, the four items that were most significant were all low levels of:

Bottom Line

SIBO by definition is OVERGROWTH, the stool samples and statistics says it is an UNDERGROWTH condition. Undergrowth means that substances do not get processed fully….

The sample size is low, more people with SIBO should transfer their data to Biomesight, then back to Microbiome Prescription, and then annotate it with SIBO. See Video on Transferring Data from Ombre/Thryve to Biomesight and then to Microbiome Prescription. I will wait until the sample size is larger before doing a formal post.

In the mean while, people with SIBO can try the new algorithm on the changing microbiome page. Feel free to add comments here on experience after trying suggestions for a month.

REMEMBER: The usual test is finding various compounds on the breath. Are the compounds from producing too much(overgrowth) or the compounds are not being consumed enough (undergrowth). Both scenarios produce a positive result. It feels like someone jumped to a conclusion and this arbitrary decision stuck in the name.

Special Studies: Bloating

This is a common symptom for people that have uploaded. This is reported often in samples, and thus being examined if it reaches our threshold for inclusion as defined in A new specialized selection of suggestions links (A summary table of various studies has been added there).

Study Populations:

  • Bacteria Detected with z-score > 2.6: found 120 items, highest value was 5.4
  • Enzymes Detected with z-score > 2.6: found 298 items, highest value was 5.4
  • Compound Detected with z-score > 2.6: found ZERO items

The highest z-scores above are less than other symptoms with smaller study sizes. The likely cause is a more diverse study population

Interesting Significant Bacteria

All bacteria found significant had too low levels.

The dominant bacteria group seems to be Bifidobacterium, low Bifidobacterium . The latter we know little about. I should point out that these bacteria may not be the cause, rather they may be ‘the canaries in the coal mine’ of the microbiome. These studies’ methodology determines association and not causality.

BacteriaReference MeanStudyZ-Score
Bifidobacterium cuniculi (species)82285.4
Bifidobacterium catenulatum subsp. kashiwanohense (subspecies)320865.4
Bifidobacterium kashiwanohense PV20-2 (strain)316865.3
Veillonella (genus)405421965
Bifidobacterium asteroides (species)58265
Haemophilus parahaemolyticus (species)68224.9
Lactiplantibacillus pentosus (species)120274.9
Bifidobacterium animalis (species)12211604.7
Bifidobacterium gallicum (species)378511114.7

Interesting Enzymes

All enzymes found significant had too low levels.

I will leave it to the reader to go to Kyoto Encyclopedia of Genes and Genomes to learn about these enzymes (a steep learning curve).

EnzymeReference MeanStudy
D-glucose-6-phosphate:NAD+ 1-oxidoreductase (
2-acetylphloroglucinol C-acetyltransferase (
ornithine lipid,2-oxoglutarate:oxygen oxidoreductase (ester-linked acyl 2-hydroxylase) (
L-tyrosine:D-ribulose-5-phosphate lyase (isonitrile-forming) (
ATP:L-threonine O3-phosphotransferase (
L-pipecolate/L-proline:NADP+ 2-oxidoreductase (

Bottom Line

The absence of Bifidobacterium is echo in several studies

REMEMBER: With your appropriate 16s sample, Dr. Artificial Intelligence on Microbiome Prescription will detail out foods, supplements et cetra to take (and to AVOID). If you do not have a sample, then review Bifidobacterium Summary Page.

Special Studies: Post-Exertional Malaise (PEM)

This is a common symptom for both ME/CFS and Long COVID. This is reported often in samples, and thus being examined if it reaches our threshold for inclusion as defined in A new specialized selection of suggestions links.

Beyond the goal of identifying bacteria involved, I am curious on the intersection of the bacteria with ME/CFS and Long COVID – i.e. bacteria in common and not in common.

Study Populations:

Post-Exertional Malaise (PEM)108662
  • Bacteria Detected with z-score > 2.6: found 181 items, highest value was 6.2
  • Enzymes Detected with z-score > 2.6: found 237 items, highest value was 7.0
  • Compound Detected with z-score > 2.6: found ZERO items

The highest z-scores above are less than other symptoms. There are two possible reasons:

  • Smaller Study Population
  • A more varied population in the study group.

Interesting Significant Bacteria

All bacteria found significant had too low levels.

We have two dominant bacteria group, both Bifidobacterium and Sporolactobacillus. The latter we know little about. I should point out that these bacteria may not be the cause, rather they may be ‘the canaries in the coal mine’ of the microbiome. These studies’ methodology determines association and not causality.

Bacteria (Rank)Reference MeanStudy Meanz-score
Sporolactobacillus (genus)174606.2
Sporolactobacillus putidus (species)174606.2
Sporolactobacillaceae (family)173606.2
Bifidobacterium cuniculi (species)81245.9
Bifidobacterium asteroides (species)58235.9
[Ruminococcus] gnavus (species)742133365.4
Mediterraneibacter (genus)787037175.3

Interesting Enzymes

All enzymes found significant had too low levels.

I will leave it to the reader to go to Kyoto Encyclopedia of Genes and Genomes to learn about these enzymes (a steep learning curve).

There are some items of special interest appearing which I drill into below.

hydrogen-sulfide:ferredoxin oxidoreductase (
D-fructose:ubiquinone 5-oxidoreductase (
D-fructosyl-L-lysine 3-epimerase (
L-tryptophan carboxy-lyase (
aromatic-L-amino-acid carboxy-lyase (
CTP:N-acylneuraminate cytidylyltransferase (
protein-Npi-phospho-L-histidine:L-ascorbate Npi-phosphotransferase (
propane-1,2-diol hydro-lyase (propanal-forming) (
N-methylhydantoin amidohydrolase (ATP-hydrolysing) (
D-ribopyranose furanomutase (
3-dehydro-L-gulonate:NAD(P)+ 2-oxidoreductase (

hydrogen-sulfide:ferredoxin oxidoreductase ( This is connected to iron. The blood uses iron to carry oxygen, and thus an absence/low level could [speculation] result in an impact on the blood’s ability to deliver oxygen (thus fatigue).

D-fructose:ubiquinone 5-oxidoreductase ( This is also connected to iron.

For those wishing to explore more, you may wish to read Oxidoreductase

It does hint at an experiment to try: After exercise, try a dosage of Ubiquinol to see if it influences things.

Common Bacteria Shifts Observed in ME/CFS

We have 45 bacteria in common, they are listed below. A LOT of them are bifidobacterium, and no lactobacillus. This implies that bifidobacterium probiotics may be a good choice for ME/CFS with PEM

Thiorhodococcus pfennigiispecies
Candidatus Tammella caduceiaespecies
Veillonella atypicaspecies
Gemella cuniculispecies
Bifidobacterium catenulatumspecies
Pedobacter kwangyangensisspecies
Haemophilus parainfluenzaespecies
Clostridium aestuariispecies
Lactococcus fujiensisspecies
Bifidobacterium bifidumspecies
Balneola vulgarisspecies
Ruminococcus flavefaciensspecies
Veillonella disparspecies
Clostridium chartatabidumspecies
Actinobacillus pleuropneumoniaespecies
Sporolactobacillus putidusspecies
Bifidobacterium kashiwanohense PV20-2strain
Bifidobacterium catenulatum subsp. kashiwanohensesubspecies
Bifidobacterium gallicumspecies
Bifidobacterium cuniculispecies
Bacteria COMMON to ME/CFS and PEM

Common Bacteria Shifts Observed in Long COVID

We have 42 bacteria in common, they are listed below. We notice some interesting difference from above:

  • Lactobacillus at the genus level as well as the retail probiotic Lactiplantibacillus plantarum (AKA Lactobacillus plantarum)
  • Bifidobacterium is still there, but one of them is available as a retail probiotics.
    • Bifidobacterium animalis
Lactiplantibacillus plantarumspecies
Flammeovirga pacificaspecies
Phocaeicola massiliensisspecies
Fusobacterium gonidiaformansspecies
Candidatus Tammella caduceiaespecies
Bifidobacterium thermophilumspecies
Dolichospermum curvumspecies
Blautia wexleraespecies
Actinobacillus pleuropneumoniaespecies
Eggerthella lentaspecies
Bifidobacterium gallicumspecies
Bifidobacterium animalisspecies
Bifidobacterium cuniculispecies
Schaalia naturaespecies
Phocaeicola sartoriispecies
Leptospira licerasiaespecies

Bottom Line

There appear to be differences between ME/CFS with PEM and Long COVID with PEM. The main difference is with Long COVID: Lactobacillus probiotics is a suggestion; for ME/CFS it is not.

Remember suggestions that are specific to your unique microbiome are available on the Microbiome Prescription web site.

Special Studies: Tinnitus (ringing in ear)

Tinnitus is not usually viewed as a microbiome issue. It was worth checking if it reaches our threshold for inclusion as defined in A new specialized selection of suggestions links. It did, hence this post

Study Populations:

Neurological-Audio:Tinnitus (ringing in ear)107573
  • Bacteria Detected with z-score > 2.6: found 129 items, highest value was 6.3
  • Enzymes Detected with z-score > 2.6: found 493 items, highest value was 7.1
  • Compound Detected with z-score > 2.6: found ZERO items

This is similar to Special Study: Histamine or Mast Cell Issues in finding no compounds, but the bacteria factor appears weaker and the enzymes is more.

Interesting Significant Bacteria

We have two dominant items that may be addressed by probiotics: Low Bifidobacterium and Low E.Coli

  • E.Coli probiotics are Symbioflor-2 and Mutaflor.
  • Bifidobacterium probiotics: we have 4 in the top group. Unfortunately none of these species are available at the retail level (that I am aware of). Checking interactions for these 4, there was no significant interactions found with common retail bifidobacterium species, just with the general genus.

Looking at Lactobacillus taiwanensis, there is a solid positive association with Bifidobacterium cuniculi and a weaker association with Bifidobacterium catenulatum subsp. kashiwanohense. There is also a weak association with two retail probiotic species: Bifidobacterium bifidum and Bifidobacterium animalis. It was interesting to note that there was no associations with any retail Lactobacillus species.

Bottom line appears to become: E.Coli probiotics, Bifidobacterium bifidum and Bifidobacterium animalis

All of the significant bacteria has too low levels.

BacteriaReference MeanStudyZ-Score
Bifidobacterium gallicum (species)37545346.3
Prevotella stercorea (species)66141026
Bifidobacterium subtile (species)82325.3
Escherichia coli (species)7161705.3
Lactobacillus taiwanensis (species)85125.3
Catenibacterium mitsuokai (species)432345.2
Bifidobacterium cuniculi (species)81285.1
Enterobacteriaceae (family)894826225
Bifidobacterium catenulatum subsp. kashiwanohense (subspecies)313715

Interesting Enzymes

As above, all levels that were found significant had too little. I will leave it to the reader to go to Kyoto Encyclopedia of Genes and Genomes to learn about these enzymes (a steep learning curve).

EnzymeReference MeanStudy
[cysteine desulfurase]-S-sulfanyl-L-cysteine:[molybdopterin-synthase sulfur-carrier protein]-Gly-Gly sulfurtransferase (
gamma-L-glutamyl-L-cysteinyl-glycine:spermidine amidase (
gamma-L-glutamyl-L-cysteinyl-glycine:spermidine ligase (ADP-forming) [spermidine is numbered so that atom N-1 is in the amino group of the aminopropyl part of the molecule] (
tRNA-uridine13 uracil mutase (
donor:hydrogen-peroxide oxidoreductase (
S-adenosyl-L-methionine:tRNA 5-(aminomethyl)-2-thiouridylate N-methyltransferase (
5-oxo-L-proline amidohydrolase (ATP-hydrolysing) (
thioredoxin:protein disulfide oxidoreductase (dithiol-forming) (
acetyl-CoA:N6-hydroxy-L-lysine 6-acetyltransferase (
UDP-alpha-D-glucose:enterobactin 5′-C-beta-D-glucosyltransferase (configuration-inverting) (
S-adenosyl-L-methionine:tRNA (uracil54-C5)-methyltransferase (
L-methionine:2-oxo-acid aminotransferase (

Interesting Compounds

Nothing was found again!!!! In one sense this was a surprise, in another sense, it hints that the results found significant are not random.

Bottom Line

This was an interesting analysis because the dominant deficiencies were in genus that are available as probiotics. In reality, it points to just 3 probiotics: an E.Coli probiotic and two bifidobacterium. Food suggestions will be generated on Microbiome Prescription using an individual’s unique microbiome.

Social Feedback

From The Gut Club: Stool Test Discussion Group

I went and looked at these two in combinations and got a lot of bacteria in common

Bacteria NameTaxonomy rank
Anaerococcus lactolyticusspecies
Negativicoccus succinicivoransspecies
Sutterella stercoricanisspecies
Lactococcus fujiensisspecies
Prevotella disiensspecies
Clostridium chartatabidumspecies
Peptoniphilus asaccharolyticusspecies
Butyricimonas synergisticaspecies
Pedobacter kwangyangensisspecies
Staphylococcus pseudolugdunensisspecies
Streptococcus millerispecies
Clostridium cellulovoransspecies
Schaalia naturaespecies
Enterobacteriaceae incertae sedisnorank
Bifidobacterium cuniculispecies
Prevotella coprispecies
Bifidobacterium gallicumspecies
Escherichia colispecies
Prevotella stercoreaspecies
Prevotella paludivivensspecies
ProForma Suggestions

Special Study: Histamine or Mast Cell Issues

This is reported often in samples, and thus being examined if it reaches our threshold for inclusion as defined in A new specialized selection of suggestions links.

Suggestions are available on Changing Microbiome tab on

Study Populations:

Histamine or Mast Cell Issues109256
  • Bacteria Detected with z-score > 2.6: found 143 items, highest value was 8.5
  • Enzymes Detected with z-score > 2.6: found 215 items, highest value was 6.1
  • Compound Detected with z-score > 2.6: found ZERO items

Interesting Significant Bacteria

One of the top items happens to have probiotics that are known to take up residency – are Symbioflor-2 and Mutaflor. . All of these top items are too low levels

BacteriaReference MeanStudyZ-Score
Prevotella paludivivens (species)140218.5
Prevotella stercorea (species)6451456.1
Escherichia albertii (species)9122325.1
Serratia (genus)10112754.9
Serratia entomophila (species)9872634.8
Alishewanella (genus)35194.7
Clostridium cellulovorans (species)40174.6
Yersiniaceae (family)10323174.6
Prevotellaceae (family)81953287334.5
Prevotella copri (species)65645139944.5
Escherichia (genus)561716644.5
Prevotella (genus)73889227714.5
Staphylococcus pseudolugdunensis (species)45204.3
Escherichia coli (species)7122344.3
Schaalia naturae (species)211374.3
Atopobiaceae (family)132394.2
Rhodovibrionaceae (family)119614.1
Bulleidia (genus)188304.1

Interesting Enzymes

As above, too low levels were most significant

EnzymeReference MeanStudy
propanoyl-CoA:oxaloacetate C-propanoyltransferase (thioester-hydrolysing, 1-carboxyethyl-forming) (
(2S,3R)-3-hydroxybutane-1,2,3-tricarboxylate pyruvate-lyase (succinate-forming) (
S-methyl-5′-thioadenosine:phosphate S-methyl-5-thio-alpha-D-ribosyl-transferase (
UDP-N-acetyl-alpha-D-glucosamine:lipopolysaccharide N-acetyl-D-glucosaminyltransferase (
(2S,3S)-2-hydroxybutane-1,2,3-tricarboxylate hydro-lyase [(Z)-but-2-ene-1,2,3-tricarboxylate-forming] (
n/a (
L-carnitinyl-CoA hydro-lyase [(E)-4-(trimethylammonio)but-2-enoyl-CoA-forming] (
acyl-CoA,ferrocytochrome b5:oxygen oxidoreductase (6,7 cis-dehydrogenating) (

Interesting Compounds

Nothing was found!!!! In one sense this was a surprise, in another sense, it hints that the results found significant are not random.

Bottom Line

Histamine or Mast Cell Issues appears to a condition of deficiency. Common internet thinking is that it is a condition of a surplus of histamine producing bacteria. It is more likely that the normal histamine consumers are being starved of enzymes that are needed to stop the accumulation of histamine.

Proforma Suggestions

Special Study: Neurocognitive: Brain Fog

This is reported often in samples, and thus being examined if it reaches our threshold for inclusion as defined in A new specialized selection of suggestions links.

This is now available on the Special Studies

Study Populations:

Neurocognitive:Brain Fog1020127
  • Bacteria Detected with z-score > 2.6: found 97 items, highest value was 5.3
  • Enzymes Detected with z-score > 2.6: found 309 items, highest value was 5.6
  • Compound Detected with z-score > 2.6: found 571 items, highest value was 5.8

Interesting Significant Bacteria

The top item happens to have probiotics that are known to take up residency – Symbioflor-2 and Mutaflor. All of these top items are too low levels

BacteriaReference MeanStudyZ-Score
Escherichia coli (species)7431685.3
Lactiplantibacillus pentosus (species)123255.1
Shuttleworthia (genus)288955.1
Escherichia (genus)590315004.5
Veillonella (genus)407225224.4
Veillonella dispar (species)8531274.4
Staphylococcus pseudolugdunensis (species)46204.2
Clostridium cellulovorans (species)40184.1

Interesting Enzymes

NADH is available as a supplement. It is reported to improve ME/CFS

EnzymeReference MeanStudy
3-phenylpropanoate,NADH:oxygen oxidoreductase (2,3-hydroxylating) (
3-(cis-5,6-dihydroxycyclohexa-1,3-dien-1-yl)propanoate:NAD+ oxidoreductase (
propanoyl-CoA:oxaloacetate C-propanoyltransferase (thioester-hydrolysing, 1-carboxyethyl-forming) (
(2S,3R)-3-hydroxybutane-1,2,3-tricarboxylate pyruvate-lyase (succinate-forming) (
[cysteine desulfurase]-S-sulfanyl-L-cysteine:[molybdopterin-synthase sulfur-carrier protein]-Gly-Gly sulfurtransferase (
ATP:D-tagatose 6-phosphotransferase (

Interesting Compounds

All of the top compounds had lower levels

2-Phospho-4-(cytidine 5′-diphospho)-2-C-methyl-D-erythritol (C11436)5.8
O-Acetyl-L-homoserine (C01077)5.4
Adenosine-GDP-cobinamide (C06510)5.4
6-Deoxy-L-galactose (C01019)5.2
[Enzyme]-cysteine (C15811)5.2
Adenosyl cobyrinate a,c diamide (C06506)5.1
Xanthosine 5′-phosphate (C00655)5.1
dTDP-glucose (C00842)5.1

Bottom Line

The z-scores for bacteria are lower than Long COVID which reflect the diffusion of bacteria over time. Trying to tackle at the compound or enzyme levels becomes excessively complex. Working at the bacteria level appears viable, but do not expect as many bacteria matches to appear.

Proforma Suggestions

A new specialized selection of suggestions based on statistical significance

Going to [Changing Microbiome] page you will see a new box appearing. It may or may not contains links to suggestions. It is scoped to BiomeSight interpretation of microbiome data. If you have Ombre/Thryve samples, do not despair, you can move your raw data to BiomeSight and send it to Microbiome Prescription. It is simple and fast as shown in this video 📹Video on Transferring Data from Ombre/Thryve to Biomrsight and then to Microbiome Prescription.

Actually, if you have done any of those listed below — you can follow the same process

Choices from
The counts are the number of matches to the sample currently selected.

What will appear in this list?

First, why Biomesight? — the reason is very simple, there are more samples (20% more at present and increasing then Ombre despite being in business for much less time). The bigger the sample size, the easier it is to find significant shifts.

The criteria is that there must be strong statistical significance for a good number of bacteria. My current threshold is: z-scores must all be 2.6 or higher, that is p <0.01 or 99% confidence. At least 50 bacteria needs to be identified as significant. I will be going thru the symptom list from most frequency reported to less frequently reported. Make sure that you annotate your samples with your symptoms.

NOTE: The numbers below reflect the statistics when various posts were done. The numbers are recomputed at least bi-weekly.

Long COVID15710.6-12-22.7
General ME/CFS1596.64.53.1
ME/CFS with IBS528.46.3n/a
Tinnitus (ringing in ear)736.37.1n/a
Histamine or Mast Cell Issues568.56.1n/a
Neurocognitive: Brain Fog1275.35.65.8
Neurocognitive: Can only focus on one thing at a time795.86.7n/a
Neurocognitive: Difficulty paying attention for along period of time755.25.0n/a
Neurocognitive: Problems remembering things696.35.9n/a
Difficulty finding the right word677.05.5n/a
Post-Exertional Malaise (PEM)626.27.0n/a
Unrefreshing Sleep1075.55.2n/a
General: Fatigue1305.25.73.9
Worsening of Symptoms with Stress.926.95.1n/a
Irritable Bowel Syndrome556.76.1n/a
Poor Gut Motility558.86.4n/a
Easily Irritated539.95.9n/a
Allergic Rhinitis (Hay Fever)428.66.8n/a
Hypersensitivity to Noise566.98.1n/a
Intolerance of Extremes of Heat and Cold548.86.7n/a
Cold Extremities7812.65.3n/a
Small intestinal bacterial overgrowth (SIBO)356.57.9n/a
Allergies And Food Sensitivity739.96.8n/a
Alcohol intolerance + Medication sensitivities598.67.9n/a
The bigger the z-score (positive or negative), the more significant
  • I should point out that these bacteria may not be the cause, rather they may be ‘the canaries in the coal mine’ of the microbiome. These studies’ methodology determines association and not causality.

An additional criteria is that they need to be clear abnormalities with the KEGG Enzymes estimate.

Enzyme (KEGG Identifier)Reference MeanLong COVID MeanZ-Score
S-adenosyl-L-methionine:16S rRNA (guanine1516-N2)-methyltransferase (
ATP phosphohydrolase (ABC-type, teichoic-acid-exporting) (
(S,S)-butane-2,3-diol:NAD+ oxidoreductase (
(S)-acetoin:NAD+ oxidoreductase (
UDP-N-acetyl-alpha-D-glucosamine:beta-D-mannosyl-glycoprotein 4-beta-N-acetyl-D-glucosaminyltransferase (configuration-inverting) (
acetyl-CoA:propanoate CoA-transferase (
Example for the enzyme shifts

I have done two with acceptable results and have made them available. More will be added over time (each one takes a fair amount of time).

US National Library of Medicine Studies are difficult to use

I have their results available and on the site, including as bacteria filters. The problem is that all of those results are very sensitive to the lab being used and the software processing the results. See The taxonomy nightmare before Christmas… for background. In the absence of better information, they are the best we have — until now. With these suggestions, the lab and the software being used are the same and also the one that your results are done by.


Interesting Observation

For both of the above, lower levels of a large number of bacteria was the common pattern. These bacteria are not present in all samples, and most of the studies seen on the US National Library of Medicine look only at bacteria found in all samples. That approach will exclude the bacteria that we find are significant.

You may find dozens (in this case 6 dozens!) of bacteria selected

A second item to be aware of is that often those PubMed studies may consist of just 50 people (control and patients). In our analysis, we have 1200+ people with often more then 120 people with a specific condition. Statistically, we are more likely to detect more associations than those studies. It’s a number’s game.

I am still tuning the suggestions engine, so expect reordering of suggestions occasionally. The suggestions pass the reasonableness test.

Quick Cross Validation

I ran the suggestions only for prescription drugs for ME/CFS and the top four suggestions are listed below. Three of the top four are used by ME/CFS physicians such as Dr. Cecile Jadin [Src], Philippe Bottero [src], G. L. Nicolson, M. Y. Nasralla, A. R. Franco, K. De Meirleir, N. L. Nicolson, R. Ngwenya & J. Haier [Src]. These physicians all report various degree of success.

  • azithromycin,(antibiotic)s
  • atorvastatin (prescription)
  • minocycline (antibiotic)s
  • doxycycline (antibiotic)s

Atorvastatin is an oddity with no studies for its use with ME/CFS. On the flip side, generic statins were high on the avoid list. It would be nice if someone did a clinical trail for this explicit type of statin.

Comparing 4 ME/CFS Samples with New Tool

A reader pinged me about new results so I thought it would be good to look at his series of 4 samples from Ombre/Thryve to help people interpret their own results. I am using the tool described in Comparing Samples – Update.

  • As you can see, the bacteria count do bounce around, with the change from the last sample being a definite improvement
  • There is a ongoing shift towards overproduction of Enzymes, but this does not cascade into increased compound (Produced – Consumed)
  • Several of the External Criteria measures showed improvement (2 less) and less showed more (1 more)

The reader has prior reviews:

Lab Read Quality4.
Bacteria Reported By Lab515669593473
Bacteria Over 99%ile0101
Bacteria Over 95%ile422219
Bacteria Over 90%ile22404821
Bacteria Under 10%ile431122387
Bacteria Under 5%ile1860546
Bacteria Under 1%ile0902
Lab: Thryve NULL
Rarely Seen 1%32090
Rarely Seen 5%1167389
Outside Range from JasonH7799
Outside Range from Medivere17172020
Outside Range from Metagenomics8877
Outside Range from MyBioma881010
Outside Range from Nirvana/CosmosId23232222
Outside Range from XenoGene881010
Outside Lab Range (+/- 1.96SD)2762
Outside Box-Plot-Whiskers42717225
Outside Kaltoft-Moldrup11314814391
Condition Est. Over 99%ile0000
Condition Est. Over 95%ile0000
Condition Est. Over 90%ile0010
Enzymes Over 99%ile9148535
Enzymes Over 95%ile599305182147
Enzymes Over 90%ile719629438458
Enzymes Under 10%ile707138169
Enzymes Under 5%ile1928478
Enzymes Under 1%ile2000
Compounds Over 99%ile69314319
Compounds Over 95%ile18627719089
Compounds Over 90%ile303435220118
Compounds Under 10%ile321528333133
Compounds Under 5%ile195378310100
Compounds Under 1%ile011826742

Bottom Line

The microbiome is a dynamic system and as shown in the image below, it is not a simple straight path. There is no single measure that indicate the current status of the gut, rather a variety of measures.

The latest sample showed (compare to prior):

  • Drop in compound extremes
  • Increase in high Enzyme production — this may hint at the body stocking up on supplies for an attack of troublesome bacteria
  • A drop of bacteria out of range by both external criteria and Microbiome Prescription Criteria.

Reader’s Comments

This round I restarted the b.lactis by custom probiotics. I did it last test and took a month break and it came up again. 1st round doing it , the herx was kicking my butt and I lasted 10 days. This time around , only did 1 scoop at night and I was still herxing and sleeping 8 hours hard. After day 10 I did half dose mornings and half at mid day or night. Much better tolerance and body seems to respond well. Calmer, better sleep, allergies seem better. 

Now also taking rice bran, blue berries, Lactoferrin for iron, and a lot of the other high priority items. I try playing basketball 1 time a week to check my progress. I have plenty of energy to play, but if I play too hard I crash still exactly 5 hours later (impaired sleep, brain fog, fatigue , headache, inflamed stomach lasting exactly 24 hours) . Then back to normal the same day. Tried the symptom /handpick bacteria tool and focused on picking PEM/brain fog/sleep with associations.  The top modifier for that was glycemic (licorice root tincture). Added that to the mix this week. Still crash, but notice some weight loss and less belly inflammation after I play. Overall improvement in sleep and anxiety. I am still a work in progress and could be better, but seeing improvement. My post exertion crashes are the thorn in my side I haven’t been able to dent much, no clue why I crash exactly 5 hours after every time but can play and feel find right after. Couple more days of b lactis and I switch to my next probiotic L.gasseri. Then will test again in about 2 weeks!

Mystery of Crash after 5 hours lasting exactly 24 hours

I have a few suggestions to try — looking at possible mechanisms..

The goal is to see if any alters the onset at 5 hrs, thus a “tell” for possible causality.

Comparing Samples – Update

A reader asked me to compared her latest sample to her prior samples. Comparing samples can be time consuming and complex, so I revisited my past comparisons posts and created a table that saves time and add clarity.

Location of the comparison table

Bacteria Report

  • Lab Read Quality indicates the numbers of bacteria that the lab obtained. In this case, the quality of the samples were similar
    • This impacts Bacteria Reported. In this case 1/14 less, and the bacteria count is about 1/14 less. If there was a severe change, then we wish to understand why
  • Bacteria Over/Under: Between samples we would like them to be reduced (less extremes). If lab quality goes down or up a lot, then the numbers may need to be adjusted for comparison.
    • We see more than a 1/14 drop, which indicates a better microbiome.

Lab Relatives

If both labs were done with the same provider, then this section will appear. In this case we see that rarely seen bacteria goes down – a good sign.

Foreign Criteria

This applies various foreign criteria to the samples. The increase of pathogen is a potential concern. I tend not to focus on pathogens because the source data usually report “higher” or “lower” only.

Microbiome Prescription Criteria

This reports on the main approaches used for generating consensus suggestions. All of them indicate little change except KM which suggests improvement.

PubMed Conditions

This uses the literature from the US National Library of Medicine to estimate likelihood of having various conditions. It is a fuzzy estimate due to the what the studies report. In this case we see good improvement across the board.

KEGG Criteria

As above, we want to reduce extreme values (represented by high and low percentiles). What we see below is very significant improvement across the board.

Bottom Line

The above are the list of my first go-to items comparing samples. If someone has followed the suggestions from Dr.A.I. between samples (or done other things), it give a quantification of the changes that occur across multiple dimensions.

In this case, we see significant improvement over a few months! It should be noted that the various external criteria show no apparent changes, the deeper dive that Microbiome Prescription does show significant positive changes.