This is a common symptom for many people. 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. We are not being specific about the type of constipation. The numbers are less than desired. If you have SIBO and a sample processed thru biomesight (if you have OmbreLab, see how to do this . 📹Video on Transferring Data from Ombre/Thryve to Biomesight ) and then add SIBO as a symptoms. The online data is recomputed once a month so it will improve identification and suggestions.

The second approach is to look at where bacteria identified as statistically significant agrees with KEGG data on Methane, Hydrogen and Hydrogen Sulfide – what is measured in breath tests.

Small intestine aspirate and fluid culture. This is currently the gold standard test for bacterial overgrowth. To obtain the fluid sample, doctors pass a long, flexible tube (endoscope) down your throat and through your upper digestive tract to your small intestine. A sample of intestinal fluid is withdrawn and then tested in a laboratory for the growth of bacteria.

Small intestinal bacterial overgrowth (SIBO) – Mayo Clinic

IMHO, the sample should go thru shotgun processing and not culturing (growth of bacteria)

“Patients with functional dyspepsia also were found to have a greater relative abundance of Streptococcus and decreases in the relative abundance of other genera such as Prevotella, Veillonella, and Actinomyces compared with control subjects, suggesting that their symptoms may be related to alterations of their microbiome at this site…. 16S ribosomal RNA (rRNA) sequencing revealed that SIBO subjects had 4-fold significantly higher relative abundance of Proteobacteria and 1.6-fold significantly lower Firmicutes than non-SIBO subjects. Furthermore, altered Proteobacterial profiles were found that correlated with symptom severity. ”

Current and Future Approaches for Diagnosing Small Intestinal Dysbiosis in Patients With Symptoms of Functional Dyspepsia [2022]

Reservation of SIBO as a Condition

I will be upfront — my motto is Ostende mihi testimonium – Show me the evidence. I do not dispute getting results from Breath Tests – but reading the latest literature [see 2022], it is likely that most of the breath tests are incorrectly done. This is especially true give the type of advice that I have seen on social media compared to the best literature (see above link). SIBO is associated with so many other conditions that I view it as a shared symptom, such as head ache or constipation. Many clinical studies are done in reference to SIBO in the context of this or that condition. This implies that researchers are seeing very different subsets in what is called SIBO. Just with the three existing breath tests, we see 3! i.e. 6 potential subtypes of SIBO – each with different bacteria involved and thus different treatment plan being likely.

In preparing this study, I attempted to disprove my gut feeling but looking for what should be there and could not find it. See below.

Study Populations:

Symptom	Reference	Study
Small intestinal bacterial overgrowth (SIBO)	1186	35

• Bacteria Detected with z-score > 2.6: found 205 items, highest value was 6.5
• Enzymes Detected with z-score > 2.6: found 335 items, highest value was 7.9
• Compound Detected with z-score > 2.6: found No items

Interesting Significant Bacteria

All bacteria was found to be low. This may suggests that bacteria that would consume Methane, Hydrogen and Hydrogen Sulfide may be deficient.

Interesting Enzymes

As with bacteria, all of the enzymes found significant were too low. We have a lot of them!

Enzyme	Reference Mean	Study Mean	Z-Score
propanoate:CoA ligase (AMP-forming) (6.2.1.17)	1884	267	7.9
all-trans-zeta-carotene:acceptor oxidoreductase (1.3.99.26)	2217	678	6.6
15-cis-phytoene:acceptor oxidoreductase (neurosporene-forming) (1.3.99.28)	2217	678	6.6
15-cis-phytoene:acceptor oxidoreductase (zeta-carotene-forming) (1.3.99.29)	2217	678	6.6
15-cis-phytoene:acceptor oxidoreductase (lycopene-forming) (1.3.99.31)	2217	678	6.6
(2S,3R)-3-hydroxybutane-1,2,3-tricarboxylate pyruvate-lyase (succinate-forming) (4.1.3.30)	1434	295	6.6
propanoyl-CoA:oxaloacetate C-propanoyltransferase (thioester-hydrolysing, 1-carboxyethyl-forming) (2.3.3.5)	1480	329	6.5
catechol:oxygen 2,3-oxidoreductase (ring-opening) (1.13.11.2)	3219	1059	6.4
5-aminopentanoate:2-oxoglutarate aminotransferase (2.6.1.48)	2360	560	6.4
(S)-3-amino-2-methylpropanoate:2-oxoglutarate aminotransferase (2.6.1.22)	2353	555	6.4
(S)-2-hydroxyglutarate:quinone oxidoreductase (1.1.5.13)	2188	423	6.3
L-carnitinyl-CoA hydro-lyase [(E)-4-(trimethylammonio)but-2-enoyl-CoA-forming] (4.2.1.149)	1445	225	6.2
glutarate, 2-oxoglutarate:oxygen oxidoreductase ((S)-2-hydroxyglutarate-forming) (1.14.11.64)	1298	221	6.2
biuret amidohydrolase (3.5.1.84)	778	266	6.1
L-carnitine,NAD(P)H:oxygen oxidoreductase (trimethylamine-forming) (1.14.13.239)	1189	218	6.1
medium-chain acyl-CoA:electron-transfer flavoprotein 2,3-oxidoreductase (1.3.8.7)	1285	226	6.1
succinyl-CoA:3-oxo-acid CoA-transferase (2.8.3.5)	1289	246	6
n/a (3.4.14.13)	1253	215	6
(2S,3S)-2-hydroxybutane-1,2,3-tricarboxylate hydro-lyase [(Z)-but-2-ene-1,2,3-tricarboxylate-forming] (4.2.1.79)	1297	312	6
RNA-3′-phosphate:RNA ligase (cyclizing, AMP-forming) (6.5.1.4)	1218	225	5.9
D-glucose:NAD(P)+ 1-oxidoreductase (1.1.1.47)	1237	222	5.9
n/a (3.4.23.49)	1306	247	5.9
(2R)-2-O-phospho-3-sulfolactate hydrogen-sulfite-lyase (phosphoenolpyruvate-forming) (4.4.1.19)	1488	217	5.9
CDP-ribitol:4-O-di[(2R)-1-glycerophospho]-N-acetyl-beta-D-mannosaminyl-(1->4)-N-acetyl-alpha-D-glucosaminyl-diphospho-ditrans,octacis-undecaprenol ribitolphosphotransferase (2.7.8.14)	2268	671	5.9
CDP-ribitol:4-O-[1-D-ribitylphospho-(2R)-1-glycerophospho]-N-acetyl-beta-D-mannosaminyl-(1->4)-N-acetyl-alpha-D-glucosaminyl-diphospho-ditrans,octacis-undecaprenol ribitolphosphotransferase (2.7.8.47)	2268	671	5.9
UDP-N-acetyl-alpha-D-glucosamine:lipopolysaccharide N-acetyl-D-glucosaminyltransferase (2.4.1.56)	1054	181	5.8
D-galactaro-1,4-lactone lyase (ring-opening) (5.5.1.27)	1676	380	5.7
hydrogen-sulfide:flavocytochrome c oxidoreductase (1.8.2.3)	1145	88	5.6
3-methylcrotonoyl-CoA:carbon-dioxide ligase (ADP-forming) (6.4.1.4)	1099	135	5.6
[SoxY protein]-S-sulfosulfanyl-L-cysteine sulfohydrolase (3.1.6.20)	1164	86	5.6
(R)-lactate hydro-lyase (4.2.1.130)	1550	290	5.6
CTP:5,7-diacetamido-3,5,7,9-tetradeoxy-L-glycero-alpha-L-manno-nonulosonic acid cytidylyltransferase (2.7.7.81)	1121	117	5.4
sulfite:oxygen oxidoreductase (1.8.3.1)	1180	82	5.4
L-kynurenine hydrolase (3.7.1.3)	989	98	5.4
glutaryl-CoA:electron-transfer flavoprotein 2,3-oxidoreductase (decarboxylating) (1.3.8.6)	1230	212	5.4
L-carnitine:CoA ligase (AMP-forming) (6.2.1.48)	1376	442	5.4
(1E,3E)-4-hydroxybuta-1,3-diene-1,2,4-tricarboxylate 1,2-hydro-lyase (2-hydroxy-4-oxobutane-1,2,4-tricarboxylate-forming) (4.2.1.83)	1038	102	5.3
alkane,reduced-rubredoxin:oxygen 1-oxidoreductase (1.14.15.3)	1068	103	5.2
glutaredoxin:hydroperoxide oxidoreductase (1.11.1.25)	988	107	5.2
n/a (3.4.21.96)	7235	4398	5.2
isoquinoline:acceptor 1-oxidoreductase (hydroxylating) (1.3.99.16)	987	112	5.2
sn-glycerol-3-phosphate:oxygen 2-oxidoreductase (1.1.3.21)	472	112	5.2
reduced coenzyme F420:NADP+ oxidoreductase (1.5.1.40)	1751	594	5.2
4-fumarylacetoacetate fumarylhydrolase (3.7.1.2)	984	124	5.1
[sulfatase]-L-cysteine:oxygen oxidoreductase (3-oxo-L-alanine-forming) (1.8.3.7)	1014	215	5.1
S-methyl-5′-thioadenosine:phosphate S-methyl-5-thio-alpha-D-ribosyl-transferase (2.4.2.28)	3707	1421	5.1
gamma-butyrobetainyl-CoA:electron-transfer flavoprotein 2,3-oxidoreductase (1.3.8.13)	1398	456	5.1
(2->6)-beta-D-fructan fructanohydrolase (3.2.1.65)	189	43	5.1
(S)-lactate:oxygen 2-oxidoreductase (1.1.3.2)	662	219	5.1
(E)-4-(trimethylammonio)but-2-enoyl-CoA:L-carnitine CoA-transferase (2.8.3.21)	1384	458	5.1
benzoyl-CoA,NADPH:oxygen oxidoreductase (2,3-epoxydizing) (1.14.13.208)	107	32	5.1
(S)-mandelate:acceptor 2-oxidoreductase (1.1.99.31)	112	34	5.1
5-dehydro-4-deoxy-D-glucarate hydro-lyase (decarboxylating; 2,5-dioxopentanoate-forming) (4.2.1.41)	972	100	5.1
2,5-dioxopentanoate:NADP+ 5-oxidoreductase (1.2.1.26)	978	127	5
ferulate:CoA ligase (ATP-hydrolysing) (6.2.1.34)	973	97	5
homogentisate:oxygen 1,2-oxidoreductase (ring-opening) (1.13.11.5)	985	116	5
ADP-glucose:D-glycerate 2-alpha-D-glucosyltransferase (2.4.1.268)	67	24	5
N,N-dimethylaniline,NADPH:oxygen oxidoreductase (N-oxide-forming) (1.14.13.8)	1030	247	5
ATP:[protein]-N6-D-ribulosyl-L-lysine 3-phosphotransferase (2.7.1.172)	1095	80	5

Significant Bacteria and KEGG modelling

To me, this is where the exploration could get interesting.

The following are consumers of these three compound according to KEGG and are statistically significant in our study, Those marked with * also produces some of these compounds. Whether a bacteria is producing or consuming may depend on what is in the microbiome environment (i.e. enzyme quantity).

• Adlercreutzia equolifaciens *
• Butyrivibrio proteoclasticus *
• Corynebacterium aurimucosum *
• Emticicia oligotrophica *
• Escherichia albertii *
• Escherichia coli *
• Haemophilus parahaemolyticus *
• Phascolarctobacterium faecium *
• Phocaeicola salanitronis *
• Pseudobutyrivibrio xylanivorans
• Ruminococcus albus *
• Streptococcus anginosus
• Streptococcus equinus
• Streptococcus oralis (A.K.A. Streptococcus dentisani)
• Streptococcus vestibularis
• Turicibacter sanguinis

My perspective is that the consumption (and production) of Methane, Hydrogen and Hydrogen Sulfide is dependent on the availability of enzymes and chemicals produced by other bacteria. Those are not measured in testing — only those three easy to test by last millennium lab tests.

Of the items above, two are potentially available as retail probiotics now, or soon:

• Streptococcus dentisani, studies: [2020] [2021] [2019] [2018]
  • Streptococcus dentisani is a common inhabitant of the oral microbiota worldwide and is found at higher levels in caries-free individuals [2021]
• Escherichia coli (Mutaflor, Symbioflor-2 (US Source, World Wide Source) )

Concerning the enzymes listed above, I will leave it to the reader to see where they occur in the following example of a KEGG metabolism diagram.

I checked PubMed if there were any studies that used KEGG data for SIBO, there was just one: Association of Differential Metabolites With Small Intestinal Microflora and Maternal Outcomes in Subclinical Hypothyroidism During Pregnancy [2022] – “KEGG pathway analysis revealed that differential metabolites were mainly involved in bile secretion, cholesterol metabolism, and other pathways”

What I find really irritating is that some of the bacteria inferred to cause SIBO lacks the genetic/genes/enzymes to produce Methane, Hydrogen or Hydrogen Sulfide. My sole comment is last millennium medical belief versus current millennium medical fact.

Bottom Line

SIBO is difficult to treat. I suspect one of the cause is going with a simplistic naïve view of this condition: It is caused by having too many producers of Methane, Hydrogen and Hydrogen Sulfide. In this study, we found the opposite — it is an absence of consumers of Methane, Hydrogen and Hydrogen Sulfide. Furthermore, the existing consumers may be inhibited in this function by the absence of enzymes needed to consume. This data is coming from downstream, so it may not apply apply fully to the small intestine – however the chemicals and enzymes flowing from the small intestine would impact a stool sample.

If the naïve view was correct, the specific bacteria would have been identified decades ago and SIBO would be resolved by a round of antibiotics targeted at them. That is not people’s experience dealing with SIBO.

The bottom citation is long and well worth reading. It covers issues well with SIBO testing.

Coincident with advances in medical science, diagnostic testing evolved from small bowel culture to breath tests and on to next-generation, culture-independent microbial analytics. The advent and ready availability of breath tests generated a dramatic expansion in both the rate of diagnosis of SIBO and the range of associated gastrointestinal and nongastrointestinal clinical scenarios. However, issues with the specificity of these same breath tests have clouded their interpretation and aroused some skepticism regarding the role of SIBO in this expanded clinical repertoire.

Small Intestinal Bacterial Overgrowth-Pathophysiology and Its Implications for Definition and Management [2022]

Measurement of breath hydrogen (H₂) and methane (CH₄) excretion after ingestion of test‐carbohydrates is used for different diagnostic purposes. There is a lack of standardization among centers performing these tests and this, together with recent technical developments and evidence from clinical studies, highlight the need for a European guideline.

… SIBO has been associated with multiple conditions including IBS, rosacea, hepatic encephalopathy, obesity, gastroparesis, Parkinson’s disease, fibromyalgia, chronic pancreatitis, end‐stage renal disease, and inflammatory bowel diseases.

H₂BT has become the most used test for SIBO in clinical practice; however, this is largely due to its ease of use, non‐invasive character and low cost and not based on evidence from clinical trials.

European guideline on indications, performance, and clinical impact of hydrogen and methane breath tests in adult and pediatric patients: European Association for Gastroenterology, Endoscopy and Nutrition, European Society of Neurogastroenterology and Motility, and European Society for Paediatric Gastroenterology Hepatology and Nutrition consensus [2022]

In short, I do not know what causes the breath test results — there is an abundance of speculation, often held to as fact. There is a absence of solid evidence. What I do know is that bacteria moves up and down in the body – think of the analogy of salmon which moves upstream against strong currents. We see strong statistical shifts in stool samples as a whole, this is evidence that hints that correction may have as a side effect, relief of SIBO.

The recent news of microclots with Long COVID with researchers looking for the same issue with Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) caused me to do this summary of my understanding.

Some literature:

• SARS-CoV-2 spike protein S1 induces fibrin(ogen) resistant to fibrinolysis: implications for microclot formation in COVID-19 [2021]
• Prevalence of symptoms, comorbidities, fibrin amyloid microclots and platelet pathology in individuals with Long COVID/Post-Acute Sequelae of COVID-19 (PASC) [2022]
• A central role for amyloid fibrin microclots in long COVID/PASC: origins and therapeutic implications [2022]
  • Of double significance for me. During one ME/CFS flare, my SPECT was read as early Alzheimer’s , a condition associated with amyloid β-protein, which agreed with some symptoms.

And in the ME/CFS world

• The Occurrence of Hyperactivated Platelets and Fibrinaloid Microclots in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) [2022]
• Chronic fatigue syndrome may be caused by mini blood clots [2022]
• Molecular Mechanisms of Neuroinflammation in ME/CFS and Long COVID to Sustain Disease and Promote Relapses [2022]

My response was simple – “Old news, but the new details is interesting“. The reason it is old, is the research from Hemex Labs and David Berg from back in the 1990’s ( Chronic fatigue syndrome and/or fibromyalgia as a variation of antiphospholipid antibody syndrome: an explanatory model and approach to laboratory diagnosis [1999]).

I’ve just realized that since I started working on my ME and working on my microbiome hypoperfusion symptoms are much worse, but they come and go which I haven’t got a handle on.  I often call it brain fog or mild brain fog.  But it manifests as memory loss, difficulty retrieving information, I’ve just been out to the supermarket and I forgot a series of things I wanted to purchase for example, which means I’ll have to go out again and by that point it would be my third trip!

It’s impossible to get a SPECT scan with correct analysis in the UK sadly, but I am more convinced now after reading your blog that hypo perfusion for me is getting worse, hence my dementia like symptoms!  Memory are often wispy or very faint as well from the last few years.

Anyway are you saying here that you recovered fully by adjusting your microbiome?  Or did you do or take anything else to get you there as well.

An email

A Model on Microclots and Microbiome

My first remission from Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) under treatment occur with two “unrelated” treatments being done concurrently. Each treatment had a 80+% success rate reported in conference papers at the time.

• Treating Hypercoagulation. My MD worked directly with Hemex labs resulting in Heparin being prescribed. Additionally, I hosted some town halls with David Berg and talked with him at conferences. My specific coagulation issue responded well to piracetam and to a lesser extent, turmeric.
• Treating an Occult Infection. This was doing the protocol for occult rickettsia developed by the Pasteur Institute for Tropical Medicine and applied successfully to people with ME/CFS by Dr. Cecile Jadin (a surgeon in South Africa — her father worked at the Institute which is why she knew of the protocol).
  • “Occult Infection” was likely the persistence of the microbiome associated with the infection (Rickettsia) and not the actual infection.

Later, some ME/CFS specialists connected the dots — the infection (whatever it was) was triggering the coagulation — hence a two prong approach was needed.

Every time that I have had a flare of ME/CFS, I have done both. Typically without any prescription drugs (but if these do not work, it is back to a friendly MD asking for specific things). The items are:

• Coagulation: Piracetam (#1 preference), Turmeric, Serrapetase, Lumbrokinease, Nattokinease
• Infections: Triphala, Olive Leaf, Wormwood often with potenators such as bromelain (which allows them to get thru fibrin deposits).

Updated for 2022

It appears that we may have a feedback loop happening.

• The coagulation results in low oxygen being delivered to the body. We know that fibromyalgia pain points are associated with hypo perfusion (low oxygen) of the tissue there. Pain is produced by chemical release. It is probable that a host of other chemical signals are sent to the body in an attempt to correct this issue.
• The chemical signals moves across the body, especially to the guts. These chemical signals to the wrong microbiome results in bacteria increasing what triggers coagulation and vascular constriction.
• The cycle repeats — for some, it quiets down, for some, it becomes uncontrolled feedback (and they keep getting worse) and for others, they are locked into a reasonable stable cycle (the living death).

Treatment Implications

With the above model, we have two goals that needs to be addressed at the same time:

• Increasing oxygen flow to the entire body. Typically this means one or more of the following:
  • Anti-coagulants – best general one is low-dosage heparin. It’s cheap and if taken sublingual, no injections are needed. For my own coagulation mutation, piracetam works as well.
  • Fibrinolytics: Typically bromelain, nattokinease, serrapetase, lumbrokinese. Fibrin deposits can prevent the passage of oxygen to the tissue.
  • Vascular dilators: My favorite is flushing niacin. I take 400 mg twice a day as a prophylactic. If I get a flush, I know it is warranted. There are others.
  • Anti-inflammatory: Having blood vessels inflamed restricts oxygen delivery. There are many choices here, likely good to rotate thru several and note any that causes significant improvement.
  • Hyperbaric Oxygen Chambers: A short term assist but does not address the cause
• Encouraging the microbiome to reform.
  • This means finding out what is there with appropriate tests, see Which Test? Is GI-MAP not enough?
  • Implementing evidence based modification (the goal of Microbiome Prescription)

None of the above is likely to occur fast. In my case, I did 8 days of the highest dosage of aspirin suggested on the bottle and ended up running up and down the walls. It persuaded my MD to do testing via Hemex labs. Taking aspirin longer is not viable. In general, it is a slow long trek. I do like to do microbiome testing periodically because it gives an objective measure of progress (i.e. more normalization of the microbiome). This has been seen with several post of people with ME/CFS who has started doing suggestions with periodic retests.

Car Analogy

The human body is fare more complex than a car, but the car analogy is a good starting point. The car is running “rough” – some possible causes:

• Fibrinolytics – clogged oil or gas filter
• Anti-coagulants – fuel stabilizer, many fuels will become jelly like or deteriorate if left a long time
• Vascular dilators – fuel or coolant lines, if pinched, the engine may not work well
• Anti-inflammatory – fuel or coolant lines have garbage in them or deteriorating or wrong size
• Feedback loop: Engine timing is off. Sparkplugs are firing too late or early
• Dashboard Dials: Sending the wrong signals (i.e. fuel gauge is not working), high RPM because you forgot to change gears, etc

Quick Lesson on Coagulation

Often there can be a weakness (DNA/SNP mutation) that makes one part less efficient. Typically, this may not cause any issue –but with the wrong sets of chemical signals, it can either overproduce items “upstream” or inhibit one step.

The diagram shows the cascade, all it takes is one weak link or a different link getting stuck on high.

Bottom Line

The biggest challenge is treating all of the factors concurrently. Many MDs will opt for a “let us try just one thing at a time”. You cannot isolate the parts and deal with just one — the signaling chemicals will keep flowing across the entire body. This approach rarely works when there are multiple feedback loops occurring. Personally, I use the flushing niacin as a feedback loop damping mechanism. If I have a cold, flu or other issues, I will add in other stuff to try to keep the loop from getting re-established.

There are 3 choices for Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) to annotate samples.

• ME/CFS (i.e. not sure if they have or do not have IBS)
• ME/CFS with IBS
• ME/CFS without IBS

We are going to combine those together to look for commonality and 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 with ME/CFS with/without IBS. This is expected because mixing conditions typically results in a more divergent microbiome population thus the scope of treatment increases.

REMEMBER: When you upload your 16s samples to add symptoms! It is how we get these special studies that appear to get a lot more results than published studies.

Study Populations:

Symptom	Reference	Study
Chronic Fatigue Syndrome (CFS/ME)	1018	159

• Bacteria Detected with z-score > 2.6: found 174 items, highest value was 6.6
• Enzymes Detected with z-score > 2.6: found 148 items, highest value was 4.5
• Compound Detected with z-score > 2.6: found 6 items, highest value was 3.1

The highest z-scores above are lower than other symptoms despite bigger sample size. It was interesting to see that some compounds reached significance (likely due to the much larger sample size)

Interesting Significant Bacteria

All bacteria found significant had too low levels. Many Bifidobacterium species are significant as well as low Prevotella copri which appears on special studies on many co-morbid symptoms. The good news, is that there is work ongoing to produce a prevotella copri probiotic.

We do see a few overgrowth These are seen only in some subsets.

• Cetobacterium (genus)
• Bacteroides rodentium (species)
• Fusobacteriaceae (family)
• Anaerolineae (class)
• Fusobacteria (phylum)

Bacteria	Reference Mean	Study	Z-Score
Bifidobacterium catenulatum subsp. kashiwanohense (subspecies)	330	61	6.6
Bifidobacterium cuniculi (species)	83	26	5.7
Tenacibaculum (genus)	28	10	5.5
Shuttleworthia (genus)	296	100	5.3
Bifidobacterium gallicum (species)	3946	937	5.3
Prevotella copri (species)	69586	21905	5.2
Sporolactobacillus (genus)	181	64	5.2
Sporolactobacillus putidus (species)	181	64	5.2
Sporolactobacillaceae (family)	179	64	5.1
Veillonella (genus)	4117	2409	5
Nitrosomonadales (order)	61	36	4.7
Clostridium chartatabidum (species)	319	70	4.6

Interesting Enzymes

Most enzymes found significant had too low levels. A few were higher, the tip ones were connected to ferredoxin. This implies over reduction of the enzyme NADP⁺ reductase. I suspect that this may impact hemoglobin (what carries oxygen in the blood), and reduces it’s ability to carry oxygen — thus producing fatigue.

• CoB,CoM,ferredoxin:H2 oxidoreductase (1.8.98.5)
• CoB,CoM:ferredoxin oxidoreductase (1.8.7.3)
• CoB,CoM,ferredoxin:coenzyme F420 oxidoreductase (1.8.98.4)
• coenzyme B,coenzyme M,ferredoxin:formate oxidoreductase (1.8.98.6)

Enzyme	Reference Mean	Study Mean	Z-Score
6-amino-6-deoxyfutalosine deaminase (3.5.4.40)	1786	766	4.5
chorismate hydro-lyase (3-[(1-carboxyvinyl)oxy]benzoate-forming) (4.2.1.151)	1762	761	4.5
S-adenosyl-L-methionine:3-[(1-carboxyvinyl)-oxy]benzoate adenosyltransferase (HCO3–hydrolysing, 6-amino-6-deoxyfutalosine-forming) (2.5.1.120)	1730	752	4.5
dehypoxanthine futalosine:S-adenosyl-L-methionine oxidoreductase (cyclizing) (1.21.98.1)	1720	753	4.5
hydrogen-sulfide:flavocytochrome c oxidoreductase (1.8.2.3)	1269	302	4.1
[SoxY protein]-S-sulfosulfanyl-L-cysteine sulfohydrolase (3.1.6.20)	1290	314	4.1
CTP:5,7-diacetamido-3,5,7,9-tetradeoxy-L-glycero-alpha-L-manno-nonulosonic acid cytidylyltransferase (2.7.7.81)	1234	315	4

Interesting Compounds

Compounds are computed from the amount produced – amount consumed by the bacteria (hence we can get negative numbers).

Names	Reference Mean	Study Mean	Z-Score
Glutarate (C00489)	2096	870	3.1
Prokaryotic ubiquitin-like protein (C21177)	224	5	2.9
[L-Glutamate:ammonia ligase (ADP-forming)] (C01281)	527	91	2.7
Adenylyl-[L-glutamate:ammonia ligase (ADP-forming)] (C01299)	527	91	2.7
4-Amino-5-aminomethyl-2-methylpyrimidine (C20267)	-23607	-16191	-2.7
D-Mannitol 1-phosphate (C00644)	18249	11478	2.6

This agrees with the research (suggesting that this model is working)

• ” Currently, growing evidence has indicated that abnormal glutamate neurotransmission may contribute to the GWI symptoms.” Emerging role of glutamate in the pathophysiology and therapeutics of Gulf War illness [2021]
• Exercise modifies glutamate and other metabolic biomarkers in cerebrospinal fluid from Gulf War Illness and Myalgic encephalomyelitis / Chronic Fatigue Syndrome [2021] ” Glutamate was significantly higher in the subgroup of postexercise GWI subjects who did not develop postural tachycardia after exercise compared to nonexercise and other postexercise groups. “, i.e. lower levels results in tachycardia
• Neurotoxicity in Gulf War Illness and the potential role of glutamate. [2020]

As well as social media

• Glutamate – One More Piece in the Chronic Fatigue Syndrome (ME/CFS) Puzzle? The Neuroinflammatory Series Pt. II [Health Rising]

Bottom Line

It is unclear if glutamine or glutamate supplement will immediately help (See Role of dietary modification in alleviating chronic fatigue syndrome symptoms: a systematic review, [2017]). In my old blog post on Glutamine (also in 2017) I wrote “The available evidence suggests that glutamine supplementation may worsen the shift of bacteria seen in CFS/FM/IBS”.

In terms of the model, glutamate is likely to help normalize the gut overtime. I would still hesitate with glutamine.

In terms of probiotics, Bifidobacterium probiotics and likely Clostridium butyricum (miyarisan) are the best candidates based on the shortage of bacteria. Only one Lactobacillus probiotic should be considered:  Lactobacillus Bulgaricus, but it is a very weak suggestion.

Remember, the purpose of these studies is to identify items to be investigated (ideally by others). The data for microbiome manipulation is incorporated in the AI Suggestions algorithm on Microbiome Prescription.

If you do not have a 16s sample (which will result in better suggestions), you can use the generic a priori suggestions linked to below.