A reader messaged me the following concern

hi ken, what would you do if there’s a massive contradiction between most of the suggestions generated by the general consensus and the suggestions generated by your new “from special studies” biomesight algorithm

The first thing that I want to point out is the warning on that page.

The main issue you may be seeing is in the selection of bacteria. With the regular selection, you focus on extreme values, i.e. top 10%, outside of standard lab ranges, outside of reference ranges from Jason Hawrelak and others. The amount outside of the reference range is used to give a weight to each bacteria for the importance of shifting. Different algorithms are used with different approaches (we do not know what the ideal one is).

With the special studies, we up-ended the algorithm. We picked the bacteria based on a simple “if the amount is above or below the reference norm+/- twice the standard deviation of the mean for the reference population and then use the z-score as the weight (the statistical significance for this bacteria)”.

This change means that a bacteria that is at the 70%ile may be included in the selection (which is very unlikely with the the first methods), and this bacteria could have a very high weight (which is based on statistical significance and NOT the difference from a mile post). A Bacteria at the 99%ile will be totally ignored if it is not statistically significant for the condition.

Statistically, I prefer the special studies approach because we are using the statistical significance of the bacteria for the significance/weight for suggestions instead of the naïve assuming that being high or low is the cause.

Bottom Line

• We pick bacteria based on statistical significance for a specific condition and not whether they are high or low in general
• We give the bacteria a weight based on statistical significance for a specific condition and not the difference from a bound.

In theory, with the identical same bacteria and counts selected for two different conditions, you will get different suggestions because the weight assigned will be different since the weight is based on the statistical significance for the condition.

I well understand the confusion of some, the model being used is getting more advanced and handling more complexities.

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. It does.

My default view is that this symptom is likely due to vesicular constriction/inflammation or “stick blood” (which contains many coagulation possibilities) resulting in low warming blood flow.

Study Populations:

Symptom	Reference	Study
Sleep: Unrefreshed Sleep	1087	78

• Bacteria Detected with z-score > 2.6: found 145 items, highest value was 12.6
• Enzymes Detected with z-score > 2.6: found 170 items, highest value was 5.3
• Compound Detected with z-score > 2.6: found No items

The highest z-scores above are more than most other symptoms. This indicates that the causes are more homogeneous bacteria shifts.

Interesting Significant Bacteria

All bacteria found significant had too low levels. The dominant genus is Prevotella with the P.Copri being usually 90% of the genus count in our reference, but only 14% of the genus count with Cold Extremities indicating that the shift is very species specific. Looking at Prevotella copri in isolation, we see the best documented ways of increasing it are: mediterranean diet, resveratrol (grape seed/polyphenols/red wine), berberine, navy bean,  Conjugated Linoleic Acid and linseed(flaxseed).

It is interesting to note that some of these are known to improve coagulation or reduces inflammation

• Therapeutic Potential of Resveratrol in COVID-19-Associated Hemostatic Disorders [2021]
• One-year consumption of a grape nutraceutical containing resveratrol improves the inflammatory and fibrinolytic status of patients in primary prevention of cardiovascular disease. [2012]
• Interaction between resveratrol and thrombin and its biological implication. [2011]
• Berberine alleviates myocardial ischemia-reperfusion injury by inhibiting inflammatory response and oxidative stress: the key function of miR-26b-5p-mediated PTGS2/MAPK signal transduction. [2022]
• Berberine as a natural modulator of inflammatory signaling pathways in the immune system: Focus on NF-κB, JAK/STAT, and MAPK signaling pathways. [2022]
• Dietary conjugated linoleic acid links reduced intestinal inflammation to amelioration of CNS autoimmunity. [2021]

Bacteria	Reference Mean	Study	Z-Score
Prevotella copri (species)	66900	3090	12.6
Prevotella (genus)	74698	21293	7.6
Prevotellaceae (family)	82172	36608	6.1
Bifidobacterium kashiwanohense PV20-2 (strain)	326	78	5.9
Bifidobacterium catenulatum subsp. kashiwanohense (subspecies)	317	78	5.8
Sporolactobacillaceae (family)	173	58	5.7
Thermosediminibacterales (order)	48	18	5.7
Sporolactobacillus (genus)	174	60	5.5
Sporolactobacillus putidus (species)	174	60	5.5
Bifidobacterium gallicum (species)	3784	783	5.5
Lactiplantibacillus pentosus (species)	123	22	5.3
Phocaeicola coprocola (species)	7584	663	5

Interesting Enzymes

Most (99%) enzymes found significant had too low levels.

Enzyme	Reference Mean	Study Mean	Z-Score
n/a (3.4.24.20)	40	16	5.3
2-acetylphloroglucinol C-acetyltransferase (2.3.1.272)	182	58	5.1
ATP:L-threonine O3-phosphotransferase (2.7.1.177)	2416	529	5

Bottom Line

In this study, one species shouts out as the cause by not being there Prevotella copri. I would really emphasis the items listed above as encouraging its growth.

It may be available “soon” as a probiotic, “The gut bacterium Prevotella copri (P. copri) has been shown to lower blood glucose levels in mice as well as in healthy humans, and is a promising candidate for a next generation probiotic aiming at prevention or treatment of obesity and type 2 diabetes.” [2021]

This article is an interesting read: The Strange Case of Prevotella copri: Dr. Jekyll or Mr. Hyde? Especially for those who think all bacteria can be classified as either good or bad.

In terms of retail probiotics suggested, the E.Coli probiotic, Symbioflor-2 is suggested.

The a priori suggestions, shown below, contains the items for P. Copri cited above.

Social Feedback

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. It does, but the degree of association (z-scores) are lower than prior special studies despite having a larger study population.

Study Populations:

Symptom	Reference	Study
Sleep: Unrefreshed Sleep	1041	107

• Bacteria Detected with z-score > 2.6: found 139 items, highest value was 5.1
• Enzymes Detected with z-score > 2.6: found 208 items, highest value was 5.2
• Compound Detected with z-score > 2.6: found 1 items, highest value was 2.8 – effectively zero when false detection rate is considered.

The highest z-scores above are less than other symptoms despite larger sample size. This indicates that the causes are more diverse and thus less homogeneous bacteria shifts.

Interesting Significant Bacteria

All bacteria found significant had too low levels.

Low Veillonella is reported in some studies associated with sleep issues with it’s consumption of lactic acid(lactate) being cited as a possible factor:

• Gut microbiota in obstructive sleep apnea–hypopnea syndrome: disease-related dysbiosis and metabolic comorbidities [2019]
• “patients with sleep disturbances were characterized by lower bacterial diversities and distinct microbial composition in comparison to those without sleep disturbances. The relative abundances of Salivarius, Veillonella, Klebsiella, and Eubacterium were independent predictors of sleep disturbances in patients.” [2021] for the specific condition studied.

Bacteria	Reference Mean	Study	Z-Score
Veillonella (genus)	4063	2282	5.1
Actinobacillus (genus)	353	133	4.9
Bifidobacterium catenulatum subsp. kashiwanohense (subspecies)	321	100	4.8
Clostridium cellulovorans (species)	40	17	4.8
Bifidobacterium kashiwanohense PV20-2 (strain)	318	100	4.8
Actinobacillus porcinus (species)	184	73	4.6
Thiobacillus thiophilus (species)	85	26	4.6

Interesting Enzymes

All enzymes found significant had too low levels.

Enzyme	Reference Mean	Long COVID Mean	Z-Score
(1->4)-alpha-D-galacturonan lyase (4.2.2.2)	2453	1074	5.2
2-acetylphloroglucinol C-acetyltransferase (2.3.1.272)	185	61	4.6
phylloquinone:disulfide oxidoreductase (1.17.4.4)	28	15	4.6
[RNA] 5′-hydroxy-ribonucleotide-3′-[RNA fragment]-lyase (cyclicizing; [RNA fragment]-3′- nucleoside-2′,3′-cyclophosphate-forming and hydrolysing) (4.6.1.19)	1596	634	4.5
CMP-N-acetyl-beta-neuraminate:beta-D-galactosyl-(1->4)-N-acetyl-beta-D-glucosaminyl-R (2->3)-N-acetyl-alpha-neuraminyltransferase (configuration-inverting) (2.4.99.6)	1682	659	4.5
propane-1,3-diol:NAD+ 1-oxidoreductase (1.1.1.202)	811	106	4.5
ATP:(Kdo)-lipid IVA 3-deoxy-alpha-D-manno-oct-2-ulopyranose 4-phosphotransferase (2.7.1.166)	1591	645	4.5

Bottom Line

The key take away is that lactate/lactic acid levels appears to be a significant contributor. The reason that it is high is the lack of lactate consumers. Removal of lactate producing probiotics from supplements appears to be a logical first step (i.e. Lactobacillus), followed by taking Vitamin B1 shortly before bed time.

• Lactate as a Biomarker for Sleep [2012]

For suggestions on lowering it, see this old post of mine in the ME/CFS context.

• Reducing Lactic Acid Producing Bacteria – LABO [2019]

The issue may not be lactate by itself, but by the form of lactate (d-lactate –> bad)

Results and conclusion: Administration of L-lactate does not influence sleep-wake cycle of experimental animals. At the same time, its artificial optical analog D-lactate induces the significant (as compared to the control) decrease in wake (34.8% to 26.5%) and increase in slow wave sleep (57.4% to 69.2%). It has been suggested that D-lactate may be the antagonist of one or several L-lactate receptors.

[D-lactate as a novel somnogenic factor?] [2020]

“Thiamine (Vitamin B1) replenishment at intravenous doses of 100 mg every 12 h resolved lactic acidosis and improved the clinical condition in 3 patients.” [1997]

“Lactomin[300 mg Lactobacillus acidophilus, 300 mg Bifidobacterium longum] was discontinued, and she was treated with sodium bicarbonate and oral antibiotics. The probiotics the patient had taken were likely the cause of D-lactic acidosis ” [2010]

For almost a decade I have suspected that there was an interaction between the microbiome and Antiphospholipid syndrome (APS) also known as Hughes Syndrome (after the MD, see below). This is also called  “sticky blood syndrome” [HealthLine]. For some researchers, it is deemed to be a significant contributor to fatigue in Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) [1999 D. Berg] and likely also applies to Long COVID. My own singleton experience seems to confirm it for myself.

A reader asked about phospholipids on Facebook today, so I revisited available literature

This article by Graham R.V. Hughes, MD, FRCP (the discoverer) in 2016 is well worth reading.

For me, APS/Hughes syndrome is very much a neurological condition. Brain function does seem to be especially targeted—the more APS patients one sees, the wider and wider the neuropsychiatric ripples spread.

APS: What Rheumatologists Should Know about Hughes Syndrome • By Graham R.V. Hughes, MD, FRCP

Of course, running off the experience of just one, or even a few people, is not the best practice. Testimonials suck because of rose color glasses, fake testimonials, mainly positive responders report, and placebo effects. So what does the literature state. First there is some literature that are general discussions without the type of detail that I would love to see:

• Crosstalk Between the Gut Microbiome and Bioactive Lipids: Therapeutic Targets in Cognitive Frailty [2020]
• Phospholipid catabolism by gut microbiota and the risk of cardiovascular disease [2013]

Then we come to this article: Phosphatidylglycerols are induced by gut dysbiosis and inflammation, and favorably modulate adipose tissue remodeling in obesity [2019] which uses one of my favorite information source, the Kyoto Encyclopedia of Genes and Genomes. “We found that PGs were positively associated with microbiomes enriched with endotoxin-synthesis genes and associated with markers of inflammation.”

• ” In antiphospholipid syndrome, a thrombotic auto-immune disorder, autoreactive T cells and antibodies cross-react with auto-antigen mimicking peptides from gut commensals which appears to contribute to the pathophysiology. ” Gut microbiota and their metabolites in cardiovascular disease, 2021

Digging further we find:

 Bacteroides thetaiotaomicron, Actinomyces massiliensis, Pseudopropionibacterium propionicum, Corynebacterium amycolatum, Ruminococcus gnavus and Roseburia intestinalis[2021] lead to the formation of pathogenic T‑cell and autoantibody responses via the cross-reactivity with autoantigens (Ro60, dsDNA and ß₂ glycoprotein I). 

The role of the microbiome in lupus and antiphospholipid syndrome [2020]

M. pneumoniae and Streptococcus spp. infections, which are among the most prevalent bacterial infections in children and young adults, were linked to the occurrence of aPL. …. an anaerobic bacterium Fusobacterium necrophorum, although a variety of other bacteria such as streptococci, staphylococci, and enterococci may be also responsible…. a specific change in the gut microbial composition in APS patients. Particularly, a decrease of bacteria belonging to the genus Bilophila and overgrowth of bacteria of the Slackia genus were shown…  enrichment by Slackia spp. and by the lower abundance of butyrate-producing Butyricimonas 

Environmental Triggers of Autoreactive Responses: Induction of Antiphospholipid Antibody Formation [2019]

More discussion of mechanism is in The Role of the Gut Microbiota in the Pathogenesis of Antiphospholipid Syndrome [2015]

Bottom Line

APS only requires one of the bacteria above to trigger it. In terms of using Microbiome Prescription, I would look at Bilophila and Butyricimonas – if below 50%ile, hand pick it, then look at Slackia, if above 50%ile then hand pick it. Check the other bacteria cited above, and if any are over 75%ile, hand pick those. “It only takes one rotten apple to spoil the barrel” seems to apply here.

I have added APS to my PubMed reference list:

Personal Observations

I checked my samples from my last ME/CFS flare and found that Bacteroides thetaiotaomicron went from 73%ile on first sample after onset, to 96%ile on second sample, down to 79%ile, then 70%ile then 20%ile a few months later with recovery and returning to work. The key triggering bacteria will likely be different for each person but you at least have a candidate list to work from.

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!

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!

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:

Bacteria	Reference Mean	Study
Shuttleworthia (genus)	273	33
Prevotella stercorea (species)	6378	31
Coprococcus eutactus (species)	7987	1463
Streptococcaceae (family)	3567	1473
Veillonellaceae (family)	17295	10944
Tissierellales (order)	4162	1457
Peptoniphilaceae (family)	4158	1456

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

• propanoate:CoA ligase (AMP-forming) (6.2.1.17)
• catechol:oxygen 2,3-oxidoreductase (ring-opening) (1.13.11.2)
• (2S,3R)-3-hydroxybutane-1,2,3-tricarboxylate pyruvate-lyase (succinate-forming) (4.1.3.30)
• propanoyl-CoA:oxaloacetate C-propanoyltransferase (thioester-hydrolysing, 1-carboxyethyl-forming) (2.3.3.5)

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.

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:

Symptom	Reference	Study
Bloating	1051	98

• 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.

Bacteria	Reference Mean	Study	Z-Score
Bifidobacterium cuniculi (species)	82	28	5.4
Bifidobacterium catenulatum subsp. kashiwanohense (subspecies)	320	86	5.4
Bifidobacterium kashiwanohense PV20-2 (strain)	316	86	5.3
Veillonella (genus)	4054	2196	5
Bifidobacterium asteroides (species)	58	26	5
Haemophilus parahaemolyticus (species)	68	22	4.9
Lactiplantibacillus pentosus (species)	120	27	4.9
Bifidobacterium animalis (species)	1221	160	4.7
Bifidobacterium gallicum (species)	3785	1111	4.7

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).

Enzyme	Reference Mean	Study Mean	Z-Score
D-glucose-6-phosphate:NAD+ 1-oxidoreductase (1.1.1.388)	79	16	5.4
2-acetylphloroglucinol C-acetyltransferase (2.3.1.272)	184	60	5
ornithine lipid,2-oxoglutarate:oxygen oxidoreductase (ester-linked acyl 2-hydroxylase) (1.14.11.58)	81	19	5
L-tyrosine:D-ribulose-5-phosphate lyase (isonitrile-forming) (4.1.99.24)	104	38	5
ATP:L-threonine O3-phosphotransferase (2.7.1.177)	2445	613	4.9
L-pipecolate/L-proline:NADP+ 2-oxidoreductase (1.5.1.21)	183	55	4.9

Bottom Line

The absence of Bifidobacterium is echo in several studies

• Effectiveness and Safety of Probiotics for Patients with Constipation-Predominant Irritable Bowel Syndrome: A Systematic Review and Meta-Analysis of 10 Randomized Controlled Trials [2022]
  • “probiotics might improve the stool consistency of patients with IBS-C and increase the number of Bifidobacteria “
• “B. animalis subspecies lactis supplementation may increase defecation frequency and, in short-term treatment, may reduce CTT in healthy adults and improve stool consistency in individuals without GIS. ” [2022]
• “Bifidobacterium adolescentis were significantly less abundant in patients with Functional Abdominal Bloating/Distention, compared with healthy controls.” [2020]

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.

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:

Symptom	Reference	Study
Post-Exertional Malaise (PEM)	1086	62

• 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 Mean	Study Mean	z-score
Sporolactobacillus (genus)	174	60	6.2
Sporolactobacillus putidus (species)	174	60	6.2
Sporolactobacillaceae (family)	173	60	6.2
Bifidobacterium cuniculi (species)	81	24	5.9
Bifidobacterium asteroides (species)	58	23	5.9
[Ruminococcus] gnavus (species)	7421	3336	5.4
Mediterraneibacter (genus)	7870	3717	5.3

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.

Enzyme	Z-Score
hydrogen-sulfide:ferredoxin oxidoreductase (1.8.7.1)	7
D-fructose:ubiquinone 5-oxidoreductase (1.1.5.14)	6.2
D-fructosyl-L-lysine 3-epimerase (5.1.3.41)	6.1
L-tryptophan carboxy-lyase (4.1.1.105)	6
aromatic-L-amino-acid carboxy-lyase (4.1.1.28)	6
CTP:N-acylneuraminate cytidylyltransferase (2.7.7.43)	5.9
protein-Npi-phospho-L-histidine:L-ascorbate Npi-phosphotransferase (2.7.1.194)	5.8
propane-1,2-diol hydro-lyase (propanal-forming) (4.2.1.28)	5.7
N-methylhydantoin amidohydrolase (ATP-hydrolysing) (3.5.2.14)	5.5
D-ribopyranose furanomutase (5.4.99.62)	5.5
3-dehydro-L-gulonate:NAD(P)+ 2-oxidoreductase (1.1.1.130)	5.5

hydrogen-sulfide:ferredoxin oxidoreductase (1.8.7.1): 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 (1.1.5.14): 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

Tax_Name	Tax_rank
Thiorhodococcus pfennigii	species
Candidatus Tammella caduceiae	species
Veillonella atypica	species
Tammella	genus
Myxococcales	order
Gemella cuniculi	species
Bifidobacterium catenulatum	species
Nannocystineae	suborder
Olivibacter	genus
Campylobacterales	order
Epsilonproteobacteria	class
Campylobacteraceae	family
Pedobacter kwangyangensis	species
Haemophilus parainfluenzae	species
Haemophilus	genus
Clostridium aestuarii	species
Sterolibacteriaceae	family
Lactococcus fujiensis	species
Bifidobacterium bifidum	species
Atopobium	genus
Balneola	genus
Balneola vulgaris	species
Balneolaceae	family
Thiobacillus	genus
Pigmentiphaga	genus
Thiobacillaceae	family
Balneolia	class
Balneolales	order
Balneolaeota	phylum
Ruminococcus flavefaciens	species
Hydrogenophilalia	class
Hydrogenophilales	order
Hydrogenophilaceae	family
Atopobiaceae	family
Veillonella dispar	species
Veillonella	genus
Clostridium chartatabidum	species
Actinobacillus pleuropneumoniae	species
Sporolactobacillaceae	family
Sporolactobacillus putidus	species
Sporolactobacillus	genus
Bifidobacterium kashiwanohense PV20-2	strain
Bifidobacterium catenulatum subsp. kashiwanohense	subspecies
Bifidobacterium gallicum	species
Bifidobacterium cuniculi	species

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

Tax_Name	Tax_rank
Paenibacillus	genus
Veillonella	genus
Actinomycetaceae	family
Lactiplantibacillus plantarum	species
Actinomyces	genus
Flammeovirga	genus
Flammeovirga pacifica	species
Flammeovirgaceae	family
Lactiplantibacillus	genus
Phocaeicola massiliensis	species
Prosthecobacter	genus
Fusobacterium gonidiaformans	species
Candidatus Tammella caduceiae	species
Gammaproteobacteria	class
Tammella	genus
Coriobacteriaceae	family
Fusobacteria	phylum
Fusobacteriia	class
Fusobacteriales	order
Coriobacteriales	order
Bifidobacterium thermophilum	species
Dolichospermum curvum	species
Blautia wexlerae	species
Atopobiaceae	family
Actinobacillus pleuropneumoniae	species
Eggerthella lenta	species
Fusobacteriaceae	family
Atopobium	genus
Schaalia	genus
Bifidobacterium gallicum	species
Eggerthella	genus
Bifidobacterium animalis	species
Aerococcaceae	family
Coriobacteriia	class
Bifidobacterium cuniculi	species
Schaalia naturae	species
Phocaeicola sartorii	species
Leptospira licerasiae	species
Leptospiraceae	family
Leptospira	genus
Leptospirales	order
Alkalibacterium	genus

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.

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:

Symptom	Reference	Study
Neurological-Audio:Tinnitus (ringing in ear)	1075	73

• 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.

Bacteria	Reference Mean	Study	Z-Score
Bifidobacterium gallicum (species)	3754	534	6.3
Prevotella stercorea (species)	6614	102	6
Bifidobacterium subtile (species)	82	32	5.3
Escherichia coli (species)	716	170	5.3
Lactobacillus taiwanensis (species)	85	12	5.3
Catenibacterium mitsuokai (species)	432	34	5.2
Bifidobacterium cuniculi (species)	81	28	5.1
Enterobacteriaceae (family)	8948	2622	5
Bifidobacterium catenulatum subsp. kashiwanohense (subspecies)	313	71	5

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).

Enzyme	Reference Mean	Study Mean	Z-Score
[cysteine desulfurase]-S-sulfanyl-L-cysteine:[molybdopterin-synthase sulfur-carrier protein]-Gly-Gly sulfurtransferase (2.8.1.11)	5326	2043	7.1
gamma-L-glutamyl-L-cysteinyl-glycine:spermidine amidase (3.5.1.78)	3212	1066	6.3
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] (6.3.1.8)	3212	1066	6.3
tRNA-uridine13 uracil mutase (5.4.99.27)	3671	1246	6.3
donor:hydrogen-peroxide oxidoreductase (1.11.1.21)	3052	869	6.2
S-adenosyl-L-methionine:tRNA 5-(aminomethyl)-2-thiouridylate N-methyltransferase (2.1.1.61)	3686	1305	6.1
5-oxo-L-proline amidohydrolase (ATP-hydrolysing) (3.5.2.9)	10180	3505	6.1
thioredoxin:protein disulfide oxidoreductase (dithiol-forming) (1.8.4.16)	3812	1301	6.1
acetyl-CoA:N6-hydroxy-L-lysine 6-acetyltransferase (2.3.1.102)	719	143	6.1
UDP-alpha-D-glucose:enterobactin 5′-C-beta-D-glucosyltransferase (configuration-inverting) (2.4.1.369)	819	141	6.1
S-adenosyl-L-methionine:tRNA (uracil54-C5)-methyltransferase (2.1.1.35)	3817	1273	6.1
L-methionine:2-oxo-acid aminotransferase (2.6.1.88)	2771	815	6.1

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

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

Bacteria Name	Taxonomy rank
Nostoc	genus
Citrobacter	genus
Anaerococcus lactolyticus	species
Streptomycetales	order
Negativicoccus succinicivorans	species
Sutterella stercoricanis	species
Streptomycetaceae	family
Negativicoccus	genus
Lactococcus fujiensis	species
Actinomycetaceae	family
Prevotella disiens	species
Prosthecobacter	genus
Clostridium chartatabidum	species
Olivibacter	genus
Peptoniphilus asaccharolyticus	species
Butyricimonas synergistica	species
Campylobacterales	order
Epsilonproteobacteria	class
Campylobacteraceae	family
Pedobacter kwangyangensis	species
Staphylococcus pseudolugdunensis	species
Enterobacterales	order
Streptococcus milleri	species
Schaalia	genus
Enterobacteriaceae	family
Mitsuokella	genus
Gammaproteobacteria	class
Prevotellaceae	family
Clostridium cellulovorans	species
Schaalia naturae	species
Enterobacteriaceae incertae sedis	norank
Blochmannia	genus
Bulleidia	genus
Bifidobacterium cuniculi	species
Prevotella	genus
Escherichia	genus
Prevotella copri	species
Bifidobacterium gallicum	species
Escherichia coli	species
Prevotella stercorea	species
Prevotella paludivivens	species

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.

Study Populations:

Symptom	Reference	Study
Histamine or Mast Cell Issues	1092	56

• 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

Bacteria	Reference Mean	Study	Z-Score
Prevotella paludivivens (species)	140	21	8.5
Prevotella stercorea (species)	6451	45	6.1
Escherichia albertii (species)	912	232	5.1
Serratia (genus)	1011	275	4.9
Serratia entomophila (species)	987	263	4.8
Alishewanella (genus)	35	19	4.7
Clostridium cellulovorans (species)	40	17	4.6
Yersiniaceae (family)	1032	317	4.6
Prevotellaceae (family)	81953	28733	4.5
Prevotella copri (species)	65645	13994	4.5
Escherichia (genus)	5617	1664	4.5
Prevotella (genus)	73889	22771	4.5
Staphylococcus pseudolugdunensis (species)	45	20	4.3
Escherichia coli (species)	712	234	4.3
Schaalia naturae (species)	211	37	4.3
Atopobiaceae (family)	132	39	4.2
Rhodovibrionaceae (family)	119	61	4.1
Bulleidia (genus)	188	30	4.1

Interesting Enzymes

As above, too low levels were most significant

Enzyme	Reference Mean	Study Mean	Z-Score
propanoyl-CoA:oxaloacetate C-propanoyltransferase (thioester-hydrolysing, 1-carboxyethyl-forming) (2.3.3.5)	1443	380	6.1
(2S,3R)-3-hydroxybutane-1,2,3-tricarboxylate pyruvate-lyase (succinate-forming) (4.1.3.30)	1395	383	5.8
S-methyl-5′-thioadenosine:phosphate S-methyl-5-thio-alpha-D-ribosyl-transferase (2.4.2.28)	3654	1517	5.4
UDP-N-acetyl-alpha-D-glucosamine:lipopolysaccharide N-acetyl-D-glucosaminyltransferase (2.4.1.56)	1008	264	5.2
(2S,3S)-2-hydroxybutane-1,2,3-tricarboxylate hydro-lyase [(Z)-but-2-ene-1,2,3-tricarboxylate-forming] (4.2.1.79)	1246	401	5.2
n/a (3.4.23.49)	1244	356	5.1
L-carnitinyl-CoA hydro-lyase [(E)-4-(trimethylammonio)but-2-enoyl-CoA-forming] (4.2.1.149)	1380	367	5
acyl-CoA,ferrocytochrome b5:oxygen oxidoreductase (6,7 cis-dehydrogenating) (1.14.19.3)	1013	302	5

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.