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.
CFS Remission 