This post is intended for researchers by pointing to bacteria whose genetics are likely significant for long COVID. The raw data is below. Preliminary z-scores indicated that they are significant (Pr < 0.01) and no filtering has occurred for False Detection Rate. Users are advised to perform their own statistics.

Note: These results are lab-specific, using the data provided by BiomeSight.

The reference site for the study is: http://longcovid.microbiomeprescription.com/, the raw data is available at: http://citizenscience.microbiomeprescription.com/

Symptom Obs	No Symptom Obs	Lab	SymptomName
152	998	biomesight	Official Diagnosis: COVID19 (Long Hauler

Bacteria	tax_rank	No Symptom Count	Symptom Count	No Symptom Frequency %	Symptom Frequency %
Lactococcus	genus	620	136	62.1	89.5
Negativicoccus	genus	461	86	46.2	56.6
Pedobacter kwangyangensis	species	354	76	35.5	50
Hydrogenophilaceae	family	480	90	48.1	59.2
Nostoc	genus	344	68	34.5	44.7
Veillonella montpellierensis	species	517	94	51.8	61.8
Rhodothermales	order	24	36	2.4	23.7
Gillisia limnaea	species	586	114	58.7	75
Tetragenococcus	genus	601	107	60.2	70.4
Gillisia	genus	592	114	59.3	75
Paenibacillaceae	family	771	133	77.3	87.5
Tetragenococcus halophilus	species	101	55	10.1	36.2
Rhodothermia	class	24	36	2.4	23.7
Hydrogenophilalia	class	479	90	48	59.2
Bifidobacterium breve	species	431	82	43.2	53.9
Thermosediminibacterales	order	72	55	7.2	36.2
Bifidobacterium choerinum	species	654	117	65.5	77
Bifidobacterium longum	species	715	129	71.6	84.9
Hydrogenophilales	order	480	90	48.1	59.2
Hydrogenophilus	genus	430	81	43.1	53.3
Rhodothermaeota	phylum	24	36	2.4	23.7

Bacteria	tax_rank	No Symptom Mean	Symptom Mean	No Symptom StdDev	Symptom Std Dev	Symptom Obs	No Symptom Obs
Porphyromonas bennonis	species	317	713	1435.9	2361.1	43	288
Clostridia	class	618307	487672	199278.7	150542.1	152	995
Insolitispirillum peregrinum	species	8259	12198	15534.5	21217.5	96	593
Sphingobacterium	genus	1125	1590	1432.3	1764.9	150	938
Sphingobacteriia	class	29634	42219	29577.8	39150.6	152	995
Lelliottia amnigena	species	922	205	2676.6	592.2	38	301
Roseburia faecis	species	13441	7122	19243.9	8796.5	152	978
Leptolyngbyaceae	family	67	266	152.6	1051.5	35	232
cellular organisms	norank	994054	988395	9012.5	5355.3	152	996
Opitutae	class	142	315	447.2	759.3	79	604
Caloramator mitchellensis	species	8162	13580	19886.9	27582.2	145	925
Leptolyngbya	genus	67	266	152.2	1051.5	35	230
Sphingobacteriaceae	family	25959	37362	26540.8	35832.1	152	994
Cytophagia	class	948	2232	2899	11229.4	150	960
Aphanizomenonaceae	family	222	124	374.4	152.8	108	653
Betaproteobacteria	class	28271	21480	26518.8	17465.6	151	993
Pseudanabaenales	order	110	230	274	973.3	41	297
Pseudanabaenaceae	family	68	230	141.9	973.4	41	297
Spirosomaceae	family	730	2282	3089.7	12178.6	127	791
Tenericutes	phylum	2507	6395	5922.1	16841.5	147	957
Puniceicoccaceae	family	139	301	443	741.7	79	599
Sutterella wadsworthensis	species	6418	10491	10990.4	13485.8	108	636
Eubacteriales	order	614586	482370	199230.3	150329.8	152	995
Dolichospermum	genus	217	125	371.1	153.2	107	646
Dialister invisus	species	4796	8035	9328.1	10909.7	105	622
Mollicutes	class	2507	6395	5922.1	16841.5	147	957
Coprococcus catus	species	1256	868	1371	850	136	804
Treponemataceae	family	1604	5448	13832.3	32843.8	37	235
Dorea formicigenerans	species	1434	914	1591	1112.9	142	902
Bacteroides eggerthii	species	8545	15385	21533.5	30777.7	57	394
Cytophagales	order	948	2232	2899	11229.4	150	960
Spirochaetales	order	1551	5448	13579.1	32843.8	37	244
Terrabacteria group	clade	721047	521084	231350.3	165314.8	152	996
Cytophagaceae	family	785	2189	2917.9	11452.3	144	907
Caloramator	genus	8859	14126	20084.9	27641.6	151	972
Spirochaetes	phylum	903	3743	10120	27201.3	54	441
Emticicia	genus	784	2553	3286.6	12937.6	112	693
Leptolyngbya laminosa	species	66	266	152.8	1051.5	35	228
Burkholderiales	order	27963	21305	26363.5	17380.9	151	993
Pedobacter	genus	8642	13041	10106	17703.6	151	980
Burkholderiaceae	family	361	197	598.7	409.8	135	886
Eubacteriales incertae sedis	norank	375	161	837.1	256.6	139	895
Butyrivibrio proteoclasticus	species	496	203	1108.1	350.5	89	657
Dolichospermum curvum	species	201	97	393.5	137.7	87	505
Desulfovibrio fairfieldensis	species	720	263	1789.3	508	43	284
Bacteroidaceae	family	300654	238983	181167	141573.4	152	995
Bacteroidia	class	426327	369089	188681.8	168273.3	152	995
Acidaminococcus	genus	984	2304	4664.6	9773.8	105	707
Bacteroidales	order	426327	369089	188681.8	168273.3	152	995
Spirochaetaceae	family	1598	5448	13805.7	32843.8	37	236
Porphyromonas asaccharolytica	species	314	1553	970.4	8744.8	43	238
Erysipelotrichaceae	family	6385	3475	10831.8	4414.9	152	993
Roseburia	genus	30033	19201	34050.4	17905.1	152	991
FCB group	clade	448905	391426	199421.4	186334	152	996
Dialister	genus	4668	7912	9234.3	10868.1	107	646
Lachnospiraceae	family	219269	176420	109155.3	81234.8	152	995
Cerasicoccus	genus	249	650	650.7	1037.4	34	250
Sphingobacteriales	order	29634	42219	29577.8	39150.6	152	995
Eubacteriaceae	family	3543	1555	7588.1	4328.8	152	989
Synechococcaceae	family	68	230	141.6	973.4	41	299
Acidaminococcus intestini	species	300	799	1051.3	2292.1	37	222
Acholeplasma hippikon	species	426	812	1052.5	2058.9	35	260
Treponema	genus	1604	5448	13832.3	32843.8	37	235
Firmicutes	phylum	657764	502820	205065.5	155846.7	152	997
Caloramator indicus	species	373	1065	2091.5	3540.5	44	373
Faecalibacterium prausnitzii	species	100109	141766	77192.1	87778	152	986
Spirochaetia	class	903	3743	10119.8	27201.3	54	441
Prevotella stercorea	species	5077	10010	18648.5	25185.5	54	406
Insolitispirillum	genus	8259	12198	15534.5	21217.5	96	593
Emticicia oligotrophica	species	785	2553	3291.1	12937.7	112	691
Lelliottia	genus	922	205	2676.6	592.2	38	301
Sphingobacterium bambusae	species	316	506	452.1	1018.8	140	825

Some recent work has identified bacteria that are associated with Autism. For a summary of method, see this post. The following are the list of bacteria seen with Ombre/Thryve samples that are annotated with Autism. There are not sufficient samples yet for specific autism characteristics – so please check your uploaded samples and update the symptoms.

Note the list is Ombre/Thryve specific and cannot be applied to other microbiome reports. There is also Bacteria to Hand-Pick for Autism with Biomesight samples

These are bacteria that you want to reduce (with one caveat — the suggestions algorithm requires the percentile to be 50%ile or more). How to hand pick them? See below the list.

Note: you may only have a few of these. They are shown in the same sequence as seen on Microbiome Tree. The LAST item is what was found to be statistically significant.

1. Proteobacteria Gammaproteobacteria Gammaproteobacteria incertae sedis
2. Pectobacteriaceae Brenneria Brenneria alni
3. Enterobacterales Enterobacteriaceae Klebsiella/Raoultella group
4. Enterobacteriaceae Klebsiella/Raoultella group Klebsiella
5. Alphaproteobacteria Hyphomicrobiales Devosiaceae
6. Alphaproteobacteria Hyphomicrobiales Hyphomicrobiaceae
7. Betaproteobacteria Neisseriales Neisseriaceae
8. Betaproteobacteria Rhodocyclales Zoogloeaceae
9. Burkholderiales Burkholderiaceae Burkholderia
10. Sutterellaceae Sutterella Sutterella wadsworthensis
11. Bacteria Proteobacteria delta/epsilon subdivisions
12. Proteobacteria delta/epsilon subdivisions Deltaproteobacteria
13. Desulfovibrionaceae Desulfovibrio Desulfovibrio piger
14. PVC group Verrucomicrobia Opitutae
15. Flavobacteriia Flavobacteriales Cryomorphaceae
16. Flavobacteriales Cryomorphaceae Cryomorpha
17. Cryomorphaceae Cryomorpha Cryomorpha ignava
18. Bacteroidetes/Chlorobi group Bacteroidetes Sphingobacteriia
19. Bacteroidetes Sphingobacteriia Sphingobacteriales
20. Sphingobacteriia Sphingobacteriales Sphingobacteriaceae
21. Bacteroidales Porphyromonadaceae Porphyromonas
22. Clostridia Eubacteriales Defluviitaleaceae
23. Eubacteriales Defluviitaleaceae Defluviitalea
24. Clostridia Eubacteriales Proteinivoraceae
25. Eubacteriales Proteinivoraceae Anaerobranca
26. Eubacteriales Lachnospiraceae Butyrivibrio
27. Lachnospiraceae Butyrivibrio Butyrivibrio crossotus
28. Lachnospiraceae Butyrivibrio Butyrivibrio fibrisolvens
29. Eubacteriaceae Eubacterium Eubacterium coprostanoligenes
30. Eubacteriales Peptococcaceae Desulfosporosinus
31. Eubacteriales Clostridiaceae Alkaliphilus
32. Clostridiaceae Clostridium Clostridium oryzae
33. Clostridiaceae Clostridium Clostridium lundense
34. Clostridiaceae Clostridium Clostridium intestinale
35. Eubacteriales Clostridiaceae Lactonifactor
36. Eubacteriales Clostridiaceae Caloramator
37. Eubacteriales Eubacteriales incertae sedis Natranaerovirga
38. Eubacteriales Eubacteriales incertae sedis [Bacteroides] pectinophilus
39. Clostridia Thermosediminibacterales Thermosediminibacteraceae
40. Terrabacteria group Firmicutes Firmicutes sensu stricto incertae sedis
41. Firmicutes Firmicutes sensu stricto incertae sedis Hydrogenispora
42. Selenomonadales Sporomusaceae Anaerospora
43. Sporomusaceae Anaerospora Anaerospora hongkongensis
44. Selenomonadales Selenomonadaceae Megamonas
45. Bacilli Bacillales Listeriaceae
46. Bacillales Listeriaceae Listeria
47. Bacilli Bacillales Bacillales incertae sedis
48. Bacillales Bacillales incertae sedis Bacillales Family X. Incertae Sedis
49. Bacillales incertae sedis Bacillales Family X. Incertae Sedis Thermicanus
50. Lactobacillales Lactobacillaceae Limosilactobacillus
51. Lactobacillaceae Limosilactobacillus Limosilactobacillus fermentum
52. Lactobacillales Lactobacillaceae Liquorilactobacillus
53. Lactobacillaceae Liquorilactobacillus Liquorilactobacillus vini
54. Cyanobacteria/Melainabacteria group Cyanobacteria Oscillatoriophycideae
55. Cyanobacteria Oscillatoriophycideae Oscillatoriales
56. Bacteria Terrabacteria group Chloroflexi
57. Terrabacteria group Chloroflexi Chloroflexia
58. Bacteria Terrabacteria group Actinobacteria
59. Terrabacteria group Actinobacteria Actinomycetia
60. Actinobacteria Actinomycetia Bifidobacteriales
61. Actinomycetia Bifidobacteriales Bifidobacteriaceae
62. Bifidobacteriales Bifidobacteriaceae Bifidobacterium
63. Bifidobacteriaceae Bifidobacterium Bifidobacterium bifidum
64. Bifidobacteriaceae Bifidobacterium Bifidobacterium asteroides
65. Bifidobacteriaceae Bifidobacterium Bifidobacterium subtile
66. Actinomycetia Propionibacteriales Nocardioidaceae
67. Actinobacteria Coriobacteriia Coriobacteriales
68. Coriobacteriia Coriobacteriales Coriobacteriaceae
69. Coriobacteriales Coriobacteriaceae Senegalimassilia
70. Coriobacteriaceae Senegalimassilia Senegalimassilia anaerobia
71. Tenericutes Mollicutes Entomoplasmatales
72. Mollicutes Entomoplasmatales Spiroplasmataceae
73. Entomoplasmatales Spiroplasmataceae Spiroplasma
74. Tenericutes Mollicutes Anaeroplasmatales
75. Mollicutes Anaeroplasmatales Anaeroplasmataceae
76. Anaeroplasmatales Anaeroplasmataceae Anaeroplasma
77. Acidobacteria Acidobacteriia Acidobacteriales
78. Acidobacteriia Acidobacteriales Acidobacteriaceae
79. cellular organisms Bacteria Elusimicrobia
80. Bacteria Elusimicrobia Elusimicrobia

To make a selection, just check the appropriate checkboxes.

This is a technical note. Recently I came across this doing analysis of Long COVID data.

Thermosediminibacterales(order)

• With Long COVID: 55/152 samples or 36.2%
• Reference (excluding Long COVID samples): 72/996 or 7.2%

This present an interesting insight on possible blinkered thinking when seeing such data. Some examples are:

• Don’t brother looking —
  • It’s a rare bacteria (just 7% of people have it…)
  • It does not occur in most Long COVID patients, not interesting
• I computed the means and standard deviations, and the difference is not sufficiently significant, so do not mention

My take is simple, it occurs FIVE times more often. I view microbiome dysbiosis are the result of the “perfect storm” or should I say “imperfect storm”. The wrong concentrations of compounds and enzymes coming together from a host of bacteria. With that dysbiosis view, a rare bacteria oddity like this, hints at a subset. This is contrary to the common view that dysbiosis is caused by a single or small group of bacteria and you can make simple either/or decisions based on their presence or lack of presence.

In the case of the long COVID data, I observed some odd (by traditional thinking) situation. A few examples:

• A 10 fold difference of frequency with the higher frequency having a higher average – the traditional expectation. More of this bacteria is growing, hence we find more often.
• A 10 fold difference of frequency with the higher frequency having a lower average, with statistical significance. This is what stopped me to re-examine my perspective, including the need to re-evaluate some blinkers.

The natural question: Determining Significance!

For most people dealing with biological data, presence or non-presence is typically a dependent factor. For example, here are some means for bacteria with the outcome being Crohn’s disease detected or not (the control case). The data will often be dropped into logistic regression.

I went back to flipping bias coins thinking and raise a beer to the memory of Bernoulli. In the above case, the expected bias is that 7.2% of the time the coin will land with a head. We try a new coin and toss it 152 times and get heads 36.2% of the time…

The hypothesis to test is whether the coin is equivalent?

• The standard deviation of the population is a simple calculation – except we need to change .50 to .362 in formula below. (P.S. The Std Dev of the population is about 1%, so a range of .342 to .382 could be tried safety)

The result is a z-score of -7.43, or clearly significant well beyond a 0.01 level. Thus the presence or lack of presence is statistically significant and should be included in any analysis (but rarely seems to be in most papers)

One of the goal of Microbiome Prescription is to stay true to source data / study. There are many studies that deal with a diet style or atypical food elements, like ‘high milk fat’. Below these wide sweeping terms may be concrete specific items that are reported in a different manner. A simple examples:

• Take Vitamin B2 (Riboflavin). Milk and beef are significant contributors
  • Dietary intake of the water-soluble vitamins B1, B2, B6, B12 and C in 10 countries in the European Prospective Investigation into Cancer and Nutrition [2009]
  • Dietary Intake and Food Sources of Niacin, Riboflavin, Thiamin and Vitamin B₆ in a Representative Sample of the Spanish Population. The Anthropometry, Intake, and Energy Balance in Spain (ANIBES) Study † [2018]

Underneath the covers of this complex microbiome engine in the human body, the impact of more beef or more milk is an increased availability of Vitamin B2.

Diets are complex concepts subject to regional interpretation. A high beef diet means more beef than a typical person… so how much is that [source]?

• If you are in China, it’s more than 1 pound of beef a month.
• If you are in Russia, it’s more than 2 pound of beef a month.
• If you are in USA, it’s more than 3.5 ounces of beef a day (so, more than a MacDonald’s Quarter Pounder every day).
• If you are in Uruguay or Argentina, it’s more than 5.5 ounces of beef a day.

When we go over to items like a Mediterranean Diet, often it can mean many things with a wide range of contents. Both of the following would meet that criteria for many people:

• One serving of cereal, two servings of citrus fruits, one servings each of eggplant, okra , green beans
• 13 servings of cereal and breads, one half apple, five servings of potatoes, 3 servings of carrots, 1 serving of onions.

The MedDiet contained three to nine serves of vegetables, half to two serves of fruit, one to 13 serves of cereals and up to eight serves of olive oil daily. It contained approximately 9300 kJ, 37% as total fat, 18% as monounsaturated and 9% as saturated, and 33 g of fibre per day.

Definition of the Mediterranean Diet; a Literature Review [2015]

The majority of studies emphasized the same key dietary components and principles: an increased intake of vegetables, wholegrains, and the preferential consumption of white meat in substitute of red and processed meat and abundant use of olive oil. However, the reporting of specific dietary recommendations for fruit, legumes, nuts, bread, red wine, and fermentable dairy products were less consistent or not reported

Differences in the interpretation of a modernized Mediterranean diet prescribed in intervention studies for the management of type 2 diabetes: how closely does this align with a traditional Mediterranean diet? [2019]

To me, a medDiet is eating traditional Greek — stuffed grape leaves, Tomato Fritters, etc with a glass of Ouzo [example] – in my younger days while I was teaching, I would have this 3-4 nights of the week.

At this point, we find that most studies involving diet deteriorates into vague hand-waving.

Can you use diet style?

This is a two sided coin. If you take recommendation for items like Luteolin, it can be translated into diet such as more celery seed, olives, blueberries. Quercetin into Cranberries and Blueberries. etc. While a high meat diet is vague — does it mean beef? pork? chicken? fish? – how much?

A logical solution is to decompose the diet into an itemized list of what the diet means by component. Then using the wonderful databases at the US Department of Agriculture develop a profile of what you are getting with this style of diet. Usually there are multiple diet suggestions, so you need to intersect them to get the true bottom line on what the diet changes should be.

Bottom Line — Use Diet Style with caution!

IMHO, it is so close to saying “Buy tech stocks for your retirement”. Without doing due diligence, you may end up with a worthless portfolio. At the bottom of the suggestions is a Flavonoid section which could be translated into food specific items.

This is an interesting case which appears to illustrate well that microbiome-agnostic prescription of antibiotics can produce horrible results. Doing a yearly 16s microbiome test will allow you to potentially negotiate with your MD to pick antibiotics that both address the MD concerns and potentially improve your microbiome as a side effect. See this post: Negotiations with your Medical Professional

My backstory:

I have used FQ antibiotics many times in the last 15 years for Chronic bacterial prostatitis..

During the last few years I was diagnosed with diverticula and had an episode of diverticulitis 3 years ago which also required antibiotics.. In the last 2 years my bloating was so severe that I was like a pregnant woman.. I am a male 40 years old.. So last July I went to the beach and caught E.Coli once again from the water or the beach.. This gave me acute infection with fever the next day.. This is where the drama starts as I ended up going to 4 different labs giving me different results and switching antibiotics for 5 months.. My gut was so bad that I’ve spend one night at the WC and another day I was stuck in traffic and I didn’t come back in time.. So embarrassing..

So January I stopped the FQs since I got a severe reaction with a set of symptoms that almost took my life.. My calf tore while being in bed, not even walking, swollen joints with fluid, tinnitus, diarrhea for 1 month, stomach ache and spasms, neuropathy, brain fog, insomnia and more..

I was sure that everything started from my gut, something triggered auto-immune along with toxicity from the drugs.. 2 months in bed.. 4 months and I barely walk with many symptoms.. What saved me initially I think was homemade Kefir I had and making myself..

Then I did the test at Biomesight and understood why and what happened.. Now I know very well that life or death starts from the gut.. 

Current State

First, I like to get a feel for where the microbiome is at from a high level. Looking at the usual health measures:

• Dr. Jason Hawrelak Recommendations guidance puts the person at the 35%ile, definitely in the concerning space
• On the Potential Medical Conditions Detected, 14 items were flagged, again concerning
• In the Bacteria deemed Unhealthy list, the following stood out

Name	Rank	Percentile	Count	Comment	More Info
[Ruminococcus] gnavus	species	95.2	27410	Not Healthy Predictor	Citation
Anaerotruncus colihominis	species	97.9	5200	Not Healthy Predictor	Citation
Bacteroides fragilis	species	86.3	17220	H02076 Bacteroides infection	Citation

Looking at the distribution by frequency, nothing really stands out.

Percentile	Genus	Species
0 – 9	14	18
10 – 19	19	34
20 – 29	19	19
30 – 39	12	14
40 – 49	15	7
50 – 59	9	15
60 – 69	13	13
70 – 79	8	15
80 – 89	10	9
90 – 99	15	18

Looking at the antibiotics list taken, I went over to the Antibiotics List for MDs page for this sample. We are using this to see which antibiotics likely helped the dysbiosis of the gut to happen.

The following were the antibiotics that he had been prescribed. I put after each the positive and negative estimates from the above page. We see a -.266 for something taken for 84 days…

• IV Cipro 1 time in hospital
• Cipro oral cycles (21 days) : 5x –  (0.194)
• Norfloxacin cycles (14 days) 6x (0.282)
• Levofloxacin : 10 days – no data
• Fosfomycin: 8 sachets – no impact
• Cefaclor cycle (14 days): 12x – negative impact (Take Estimate:  35.1, Avoid Estimate:  39) (0.079)
• Amoxicillin / Clavulanic Acid cycles (21 days): 4x  ( – 0.266 )
• Cefixime cycle (24 days) : 1x  ( – 0.114 )
• Trimethoprim / Sulfamethoxazole : 3 days  (0.128) /   ( – 0.604 )
• Doxycycline: 2 days  ( – 0.173 )

In this case, it is clear from the data above that the antibiotics were a factor for his problems. if he must take antibiotics again (or can persuade his MD to do a trial), the best ones suggested by the Artificial Intelligence algorithms are:

1. rifaximin (antibiotic)s   (1)
2. metronidazole (antibiotic)s   (0.887)
3. ampicillin trihydrate (antibiotic)   (0.834)

Action Plan Going Forward

The KEGG AI Computed Probiotics had the HIGHEST VALUES that I have ever seen with the top items being, I would go for three of these (2 weeks of one, then rotate to the next, repeat): Something that lists bacillus subtilis as the first ingredient, miyarisan (jp) / miyarisan, something that is just lactobacillus plantarum (i.e. 299v)

Bacteria Name	Weight
BIO-BOTANICAL RESEARCH / Megacidin [bacillus coagulans, bacillus subtilis]	4285.54
miyarisan (jp) / miyarisan [clostridium butyricum miyairi]	4130.42
enviromedica terraflora sbo probiotic [bacillus clausii, bacillus coagulans,bacillus megaterium bacillus pumilus, bacillus subtilis]	3724.82
INVIVO THERAPEUTICS / Bio.Me IB + [bacillus subtilis, enterococcus faecium]	3716.08
CustomProbiotics.com / L. Plantarum Probiotic Powder [lactobacillus plantarum]	3324.66

For supplements, we have (even at 20%) a short list. Usually supplements can be taken consistently.

• beta-alanine – Percentile: 5.2
• Glycine – Percentile: 3
• L-Cysteine – Percentile: 10.4
• L-glutamine – Percentile: 15.5
• Magnesium – Percentile: 3.7
• Molybdenum – Percentile: 0.9

Building Consensus Suggestions

Remember, no one knows how to pick the best bacteria to target. We apply multiple criteria and then work from what is agreed upon with the different approaches (i.e. consensus).

•  Use JasonH (15 Criteria) – 11 bacteria picked (and the same for the other ones at the top of this list)
•  Standard Lab Ranges (+/- 2 Std Dev) – 24 bacteria picked
•  Box Plot Whisker – 58 bacteria picked
•  Kaltoft-Moltrup Normal Ranges – 89 bacteria picked
•  Percentile in top or bottom 10 % – 101 bacteria picked

The consensus list is long with 534 items (typical). My main take away

• Eliminate/Avoid the following:
  • high red meat / high-protein diet / high animal protein diet /high saturated milk fat diet/ milk-derived saturated,fat / animal-based diet / rare meat / fat
    • Dairy related: Cottage Cheese / Kombucha (home-made) / enriched butter diet
  • low energy diet/ calorie restriction / low carbohydrate diet / gluten-free diet
  • stevia / saccharin / chitosan,(sugar) / high sugar diet
  • broccoli / Sauerkraut
  • alcoholic beverages
• Take or Increase:
  • inulin (prebiotic) / chicory (prebiotic) / oligofructose (prebiotic)
  • high fiber diet / fruit/legume fibre / brown rice / whole-grain barley /whole-grain wheat / barley,oat
  • walnuts
  • Cacao
  • Vitamins and Supplements
    • Vitamin B-12 (Cyanocobalamin)
    • grape polyphenols / grapes (but no wine!) / polyphenols
    • from above: magnesium (found in consensus too with positive value), molybdenum and from consensus: selenium and zinc. But no iron supplements.
  • Probiotics
    • All of the items cited above are on the to take list (and many more), but the ones above are IMHO, “double blessed”
• A reminder, the items are based on the term that various studies used. In some cases, there can appear to be contradictions. In some cases this could be due to what was measure or not measured in the study as well as sample size. We do not know what is “right” when this happens, it drops into a state called “indeterminate”. There are some of those here, but also some very clear items like high fat beef.

Bottom Line

Given the severity of this person, I suggest trying suggestions for 2-3 months and then gets retested. I expect significant changes — but that is likely just a course correction. We need to do more course corrections to get back to a safe harbor.

ALWAYS REVIEW WITH YOUR MEDICAL PROFESSIONAL BEFORE STARTING

Using novel technics for my earlier post Bacteria Shifts Seen in Long COVID caused me to look at it’s sibling: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Since we have a much large sample size, we can get more rigorous and be lab specific (see The taxonomy nightmare before Christmas…). The result are the three tables below. The criteria for shift was a difference of 4 percentile or more.

Biomesight

Tax_name	Tax_rank	Sample Frequency of Detection	Population Frequency of Detection	Shift
Phocaeicola plebeius	species	12	5.2	Lower
Oscillatoriales	order	13.5	5.1	Lower
Bacteroides gallinarum	species	13.5	4.5	Lower
Aerococcaceae	family	14.1	4.5	Lower
Phocaeicola coprocola	species	15.1	5.4	Lower
Desulfovibrio	genus	22.9	8.8	Lower
Collinsella	genus	25	8.7	Lower
Hathewaya	genus	30.2	10.6	Higher
Bacteroides ovatus	species	30.2	10.6	Higher
Anaerotruncus colihominis	species	30.2	10.4	Higher
Bacteroides rodentium	species	30.2	10.6	Higher

OmbreLabs / Thryve

Tax_name	Tax_rank	Sample Frequency of Detection	Population Frequency of Detection	Shift
Alteromonadaceae	family	9.4	3.4	Lower
Paenibacillus	genus	12	6.6	Lower
Phocaeicola plebeius	species	12	7.1	Lower
Bacteroides gallinarum	species	13.5	7.3	Lower
Oscillatoriales	order	13.5	4.8	Lower
Planococcaceae	family	13.5	6.7	Lower
Aerococcaceae	family	14.1	6.8	Lower
Phocaeicola coprocola	species	15.1	7.5	Lower
Turicibacter sanguinis	species	15.1	5.1	Lower
Sarcina	genus	19.3	0.4	Lower
[Ruminococcus] torques	species	19.8	8.1	Lower
Desulfovibrio	genus	22.9	7.2	Lower
Ruminiclostridium	genus	22.9	8.2	Lower
Peptostreptococcaceae	family	24	8.2	Lower
Collinsella	genus	25	7.2	Lower
Anaerostipes	genus	26.6	8.3	Lower
Eubacterium	genus	29.2	8.3	Lower
Eubacteriales incertae sedis	norank	29.7	8	Lower
Clostridium	genus	30.2	8.2	Higher
Sphingobacteriales	order	30.2	4.8	Higher
Blautia hansenii	species	30.2	5.3	Higher
Oscillospira	genus	30.2	0	Higher
Bacteroides ovatus	species	30.2	7.2	Higher
Anaerotruncus colihominis	species	30.2	6.7	Higher
Blautia wexlerae	species	30.2	8.3	Lower
Bacteroides rodentium	species	30.2	7.4	Higher
Sphingobacteriia	class	30.2	4.8	Higher
Sphingobacteriaceae	family	30.2	4.8	Higher
Hathewaya	genus	30.2	4.1	Higher
Anaerofilum	genus	30.2	4.2	Higher
Actinobacteria	phylum	30.2	8.3	Lower

uBiome

Tax_name	Tax_rank	Sample Frequency of Detection	Population Frequency of Detection	Shift
Planococcaceae	family	13.5	0.3	Lower
Bacteroides gallinarum	species	13.5	0.1	Lower
Oscillatoriales	order	13.5	0.1	Lower
Aerococcaceae	family	14.1	0.6	Lower
Phocaeicola coprocola	species	15.1	0.4	Lower
Turicibacter sanguinis	species	15.1	3.3	Lower
Sarcina	genus	19.3	5.4	Lower
Ruminiclostridium	genus	22.9	0.2	Higher
Adlercreutzia equolifaciens	species	22.9	3.8	Lower
Desulfovibrio	genus	22.9	2.7	Lower
Peptostreptococcaceae	family	24	5.6	Lower
Collinsella	genus	25	5.5	Lower
Anaerostipes	genus	26.6	5.6	Lower
Eubacterium	genus	29.2	1.1	Higher
Eubacteriales incertae sedis	norank	29.7	5.5	Lower
Oscillospira	genus	30.2	4.2	Higher
Anaerotruncus colihominis	species	30.2	2.1	Higher
Blautia wexlerae	species	30.2	5.4	Lower
Bacteroides rodentium	species	30.2	0.1	Higher
Sphingobacteriia	class	30.2	0.1	Higher
Sphingobacteriaceae	family	30.2	0	Higher
Anaerofilum	genus	30.2	1.8	Higher
Actinobacteria	phylum	30.2	5.6	Lower
Bacteroides ovatus	species	30.2	2.9	Higher
Clostridium	genus	30.2	5.5	Higher
Sphingobacteriales	order	30.2	0.1	Higher
Blautia hansenii	species	30.2	1.8	Higher

Common across all labs

Amount of Bacteria

For the amount of shift, the nightmare described in The taxonomy nightmare before Christmas… comes true!

Tax_name	Tax_rank	Ombre	Biomesight	uBiome
Paenibacillus	genus	Lower	Higher	Higher
Phocaeicola plebeius	species	Lower	Higher	Higher
Oscillatoriales	order	Lower	Higher	Higher
Planococcaceae	family	Lower	Higher	Higher
Phocaeicola coprocola	species	Lower	Higher	Higher
Turicibacter sanguinis	species	Lower	Higher	Higher
Sarcina	genus	Lower	Higher	Higher
Bacteroides gallinarum	species	Lower	Lower	Higher

Frequency of Detection

Here we have agreement across all of the labs

Tax_name	Tax_rank	Ombre	Biomesight	uBiome
Paenibacillus	genus	More	More	More
Phocaeicola plebeius	species	More	More	More
Bacteroides gallinarum	species	More	More	More
Oscillatoriales	order	More	More	More
Planococcaceae	family	More	More	More
Phocaeicola coprocola	species	More	More	More
Turicibacter sanguinis	species	More	More	More
Sarcina	genus	More	More	More
Aerococcaceae	family	More		More
Desulfovibrio	genus	More		More
Ruminiclostridium	genus	More		More
Peptostreptococcaceae	family	More		More
Collinsella	genus	More		More
Anaerostipes	genus	More		More
Eubacterium	genus	More		More
Eubacteriales incertae sedis	norank	More		More
Clostridium	genus	More		More
Sphingobacteriales	order	More		More
Blautia hansenii	species	More		More
Oscillospira	genus	More		More
Bacteroides ovatus	species	More		More
Blautia wexlerae	species	More		More
Sphingobacteriia	class	More		More

What does all of this mean?

It means that the bacteria count may be a little bit of a red herring. It is the frequency of detection that may be a better criteria for what is significant.

To put this in human terms, for a political movement, looking at the bank account may not be the best way of detecting if it is significant; it is the number of different types of people that turns up at meetings!

The mathematics and number crunching becomes more complex… but we are dealing with a complex system. For example, if you are using uBiome and many of the following was detected, then the odds of having ME/CFS is significant. It suggests a different criteria for selecting bacteria to generate suggestions.

• Planococcaceae
• Bacteroides gallinarum
• Oscillatoriales
• Aerococcaceae
• Phocaeicola coprocola
• Turicibacter sanguinis

Returning to Long COVID

Below is NOT the amount of bacteria, it is the frequency that these bacteria were detected in the samples. In other words, there is a group of bacteria that blooms – they show up more frequently, not necessarily in larger numbers, just there — trouble makers!

Bacteria Identified in Long COVID	Ombre ME/CFS	Biomesight ME/CFS	Ubiome ME/CFS
Micrococcaceae	More	More	More
Peptostreptococcaceae	More	More	More
Butyricimonas virosa	More	More	More
Sarcina	More	More	More
Enterobacter	More	More	More
Lactobacillaceae	More	More	More
Coriobacteriia	More	More	More
Slackia faecicanis	More		More
Rhodovibrionaceae	More		More
Blautia wexlerae	More		More
Salinicoccus luteus	More		More
Staphylococcaceae	More		More
Bifidobacteriales	More		More
Holdemanella biformis	More		More
Coriobacteriales	More		More
Holdemanella	More		More
Eubacteriales incertae sedis	More		More
Fusobacteriia	More		More

This analysis shows a very similar pattern in the microbiome between Long COVID and ME/CFS.

The back story for this person is long and detailed — with a massive number of tests and conditions done! This is a much shorten version

Back Story

Male, 40yrs of age. Very physically active and successful engineer & businessman prior to illness onset 7 years ago at 33yrs of age.

Illness onset summary:

• July 2014 I had bad flu symptoms: very fatigued and bad cough, which took a couple of months to seemly recover from, albeit still had bouts of mild fatigue and random mild cough.
• September 2014 I moved into a moldy / water damage building.
• October 2014 I had the flu again. Did seem to recover.
• 2015 On-going random fatigue and insomnia, which is persistent to today.
• Sometime during this 2014/2015 period whilst living in moldy house I had a circular red rash (similar to erythema migrans) on my forearm indicating insect bite mark. Took 2 weeks to go away. Did not take photo and did not notice any symptoms during this time. I had not travelled anywhere during this time.
• I have for +7yrs managed my symptoms by predominately eating carnivore diet, regular fasts, and having daily water enemas as it is the only way I can pass stool. Start of 2020 I had to stop working all together due to extreme fatigue and brain fog. I have dedicated 100% of my limited energy to my treatment ever since.

I have seen over 17 Health Professionals of various specialities, with numerous treatments with no real improvement. First four years was predominately about treating the gut (which is still my main symptom) with various SIBO treatments, including herbs (e.g. oregano), antibiotics (Erythromycin, Rifaximin & Vancomycin), antifungals (nystatin) and seven Faecal Matter Transplants (FMT), with no success. Have had multiple endoscopy and colonoscopies with no major findings other than removal of some polyps, and negative to Whipple’s PCR albeit +ve antibodies. Many stool samples with no detected parasites.

End of 2019 I identified that Lyme and/or mycotoxin (mold) toxicity could be the cause, and in 2020 was diagnosed with Chronic Inflammatory Response Syndrome (CIRS) from mycotoxin toxicity due to various test results, and subsequently also Mast Cell Activation Syndrome (MCAS) and Cell Danger Response (CDR). I have been treating this for +24 months via various treatments e.g. binders and antifungles, although can’t tolerate most e.g. CSM, nystatin, Amphotericin B, Itranconazole. I did see some initial improvement with charcoal & bentonite which I occasionally still take when herxing, but no noteworthy improvements in symptoms.

My Lyme antibody test results are equivocal with only some IgM +ve results. I did initially respond well to doxycycline but these improvements only lasted 2 weeks. After using it on and off for other a year I can’t tolerate it for longer than 5 days or so. Cannot tolerate azithromycin and erythromycin cause severe large bowel pain, as do many other herbs e.g. Cowden protocol.

Often my bowel pain gets bad enough that pain killers are not enough so I go back on doxy as that has been the only thing helps, but I can’t stay on doxy as it makes me feel horrible after eating (which is when I take it).

Multiple hair analysis indicate that mercury distribution could be an issue, and I have had negative cognitive symptoms to single thiol chelators i.e. chlorella and EDTA. EDTA does make me feel like I’m loosing my mind. Recently start 5mg dosage of OSR which does make me more fatigued and worsen digestion.

My condition only seems to get worse and am not able to tolerate any treatments anymore.

Reinvestigating my gut biome I have taken Biomesight stool sample (whilst taking doxycycline) to see if there is any pre/probiotics I can take that will help, and considering Phage therapy and or retrying FMT treatment.

Note I’ve tried many prebiotics all of which have exacerbated my symptoms e.g. bloating, toxicity, bowel pain fatigue, brain fog etc as do most plants, hence carnivore diet, and many probiotics most of which make no difference or make me very fatigued e.g. Megaspore (presumably due to histamine).

Analysis

See the YouTube for more information and walk thru.

Using Health Analysis Page

• Health Status – 2 Healthy, 9 Unhealthy
• Jason Hawrelak – at 56%ile , significant issues
• Potential Medical Conditions Detected – a massive list!!!

In short, OUCH!

Looking at the bacteria called out especially:

• Bacteroidia / Bacteroides really dominate everything, at 70% and 60% respectively.
• Some known unhealthy bacteria with concerning values include
  • [Ruminococcus] gnavus
  • Anaerotruncus colihominis
  • Blautia producta
  • Clostridium
  • Parabacteroides
  • Streptococcus pseudopneumoniae
  • Streptococcus oralis

First Probiotics

I am finding that this is a friendly start point because we have multiple logics available to determine them (which, of course, can result in disagreement). The list is very close to the common pattern seen with ME/CFS patients:

• KEGG AI Computed
  • miyarisan (jp) / miyarisan – clostridium butyricum (probiotics)
  • enviromedica terraflora sbo probiotic (5 bacillus mixture)
  • L. Plantarum Probiotic
  • symbiopharm / symbioflor 1
  • L. Casei Probiotic
  • L. Rhamnosus Probiotic

Looking at probiotics based on dominant symptoms we see one is on the list above

• L. Plantarum Probiotic
•  L. Reuteri Probiotic
•  L. Helveticus
  

From top of the Safest Take list from Consensus Report below

• bacillus subtilis (probiotics)
• lactobacillus casei (probiotics)
• lactobacillus reuteri (probiotics)
• pediococcus acidilactic (probiotic)
• clostridium butyricum (probiotics)
• lactobacillus paracasei (probiotics)
• bacillus coagulans (probiotics)

The lists are effectively identical! One list was obtain solely by looking at the DNA of the bacteria in your sample and the DNA of the bacteria in the probiotics. The last list was generated from clinical trails reporting shifts of bacteria from taking probiotics. It appears to confirm that the novel experimental DNA produces good results.

I am pleased with that, because our depth of knowledge is actually far greater with DNA. This also allows us to evaluate new probiotics quickly without needing to wait for clinical studies and publications.

Consensus Report

As has become my custom, I whipped thru all of the suggestions using expert criteria.

•  Use JasonH (15 Criteria) – 10 matches
•  Use Medivere (54 Criteria) – 10 matches
•  Use Metagenomics (59 Criteria) – 10 matches
•  Use Nirvana/CosmosId (36 Criteria) – 10 matches
•  Use XenoGene (22 Criteria) – 10 matches
•  Standard Lab Ranges (+/- 2 Std Dev) – 15 matches
•  Box Plot Whisker – 47 matches (10%)
•  Kaltoft-Moltrup Normal Ranges – 111 matches (23%)
•  Percentile in top or bottom 10%ile – 122 matches (25%)

Looking at the consensus number of suggestions for the above, the numbers were similar, suggesting that despite the differences number of bacteria selected, the suggestions were likely similar.

Takes

My personal pick of the top suggestions are below (excluding probiotics cited above):

• Cacao (i.e. 85% Chocolate or higher) – studies have shown that it helps ME/CFS
• walnuts
• soy
• whole-grain barley (high fiber diet)
• Burdock Root
• garlic (allium sativum)
• brown rice
• black raspberries
• lauric acid(fatty acid in coconut oil,in palm kernel oil,) – a.k.a. monolaurin in some markets

This leads to the regular suggestion frequently seen with ME/CFS patients: Start each day with barley porridge with walnuts and appropriate yogurt. Note: Oats is on the safest list too, but less studied.

As a side note: meat and beef do not occur anywhere on the safest list. milk-derived saturated,fat and high saturated milk fat diet does — which suggests that whole milk should be the preferred milk (if milk is taken)

Avoids

The following items caught my eye on the highest risk items:

• high red meat, fat, rare meat, high beef diet,high animal protein diet
• glycyrrhizic acid (licorice)
• saccharin, stevia, sugar, xylitol, Manuka Honey
• linseed(flaxseed), Psyllium (Plantago Ovata Husk)— note: some commercial porridge mixtures include this — read the labels!
• oolong teas, ku ding cha tea
• broccoli, Carrot (juice), pulse
• Miso, Fish Sauce (so type of soy is important) – I would likely keep to the traditional Japanese desert Natto (if you can get it – it is a n acquired taste)
• kombucha, Kombucha (home-made), kefir, Cottage Cheese, Sauerkraut

I must point out that many items above are on the “internet-myth” always good to fix the gut list.

The avoid probiotics are:

• symbioflor 2 e.coli probiotics
• colinfant e.coli probiotics
• bacillus laterosporus (probiotic)
• bifidobacterium pseudocatenulatum li09,
• bifidobacterium catenulatum li10 (probiotics)
• Lactobacillus salivarius UCC118
• Prescript Assist (Original Formula)

It is left to the reader to go thru the lists. The list suggestion counts, from safest to most avoid, was (258, 88, 33, 52, 33,101) – so full of strongly to take…

I should point out that the complete list is available for download. I would suggest downloading it and then check everything in the diet against the list.

The land of Supplements

The AI Kegg items detected as being low are:

• Glycine – Percentile: 3
• L-glutamine – Percentile: 2.1
• L-Threonine – Percentile: 9
• magnesium – Percentile: 0.7
• Molybdenum – Percentile: 3.8

I downloaded the list from consensus and put their results below

• Glycine – Take: 9, Avoid:0
• L-glutamine – Take: 0, Avoid 4
• L-Threonine – No information
• magnesium – Take: 9, Avoid 0
• Molybdenum – No information

So two are clear additions, two are good candidates to try as an experiment, one has some risk.

Vitamins – Consensus]

To save typing I am using (Take/Avoid) counts

• Selenium (9/0)
• Magnesium (9/0)
• Vitamin B12 (8/1)
• folic acid,(supplement Vitamin B9) (7/2)
• vitamin d (6/3)
• Zinc (7/2)
• Vitamin B,E, and K2 were weak takes (3/0)

The following have higher Avoid counts than take counts, and should likely be avoided

• pyridoxine hydrochloride (vitamin B6)
• retinoic acid,(Vitamin A derivative)
• thiamine hydrochloride (vitamin B1)
• vitamin b3 (niacin)
• vitamin b7 biotin (supplement) (vitamin B7)
• Vitamin C (ascorbic acid)
• Silver
• iron

Remember — beware people telling you what is good for you! A mother recently message me. She started the suggestions and everything was going ok and then she listened to a random suggestion.

Prescription Drugs

I decided to do a consensus report on prescription items. This is done on Advance Suggestions page. I checked the following items:

And then went thru the same expert choices as above.

The results are actually more items as shown below’

I was amused, with some of these results for the alternative substances:

• gentamicin (antibiotic)s – wide spectrum antibiotics
• imipenem (antibiotic)s – wide spectrum antibiotics
• metronidazole (antibiotic)s – often prescribed by ME/CFS MDs
• piperacillin-tazobactam (antibiotic)s
• trimethoprim (antibiotic)s
• fluoroquinolone (antibiotic)s – often prescribed by ME/CFS MDs
• owning pet
• Titanium Dioxide (E171) (TiO2) Miscellaneous, food additives, and other odd items

He mentions some antibiotics that he was on without apparent success

• Erythromycin, – a mild take (5/0), impact ratio is 4:1
• Rifaximin – a stronger take (7/0) impact ratio is 2:1
• Vancomycin – a mix result (6/1) impact ratio is 2:1
• Doxycycline – (3/4), impact ratio is 3:2 (net positive)
  • Minocycline – (7/0) impact ratio is 2.5:1 and is suggested as a replacement. I checked all of the tetracycline family and this was the best one.

The nice thing is that none made him worst. I leave it to him to lookup the use, side-effects of the best suggestions and then see if he can persuade his MD to do off-label prescriptions. My usual suggestion is to follow Cecile Jadin approach and do rotation: 7-10 days on, 2 weeks off, take a different one, repeat.

Bottom Line

My intent is to show you how to use the data available. “To teach you to fish“. As you try fishing your skill level will improve and you may be able to teach others to fish.

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

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

Bottom line, my time is better spent for everyone in building the data and the methods, not in dealing with a small number of clients (thus relationships will go undiscovered and/or data becoming stale). If you want or need hand holding — there are many that will gladly do it for a fee, some uses this site and others use University Training from 1990.

There is a Long COVID Study in progress via the cooperation BiomeSight.com and Microbiome Prescrption. The data is not yet processed for the study, but we have some interest results already from those that uploaded their samples and marked Long COVID as a symptom.

Bacteria	Taxonomy Rank	Average Percentile	Frequency Seen in this Group	Frequency Seen in All Samples
Micrococcaceae	family	19	45.8	36.5
Actinobacteria	phylum	19.7	100	99.7
cellular organisms	norank	20	100	99.9
Adlercreutzia equolifaciens	species	20.1	62.5	42.8
Peptostreptococcaceae	family	22.8	95.8	96.5
Butyricimonas virosa	species	23.3	41.7	38.8
Sarcina	genus	24.7	45.8	52.4
Enterobacter	genus	25.1	41.7	23.6
Lactobacillaceae	family	26	95.8	94.9
Coriobacteriia	class	27	100	99
Actinomycetia	class	27.6	100	99.2
Adlercreutzia	genus	27.8	66.7	45.3
Slackia faecicanis	species	28	37.5	11.8
Bifidobacterium adolescentis	species	28.1	79.2	31.4
Rhodovibrionaceae	family	28.4	37.5	0
Blautia wexlerae	species	29.2	100	94.4
Anaerostipes	genus	29.7	95.8	96.1
Salinicoccus luteus	species	30.9	37.5	12.6
Staphylococcaceae	family	30.9	62.5	40.4
Bifidobacteriales	order	31.2	100	89.7
Holdemanella biformis	species	31.3	66.7	32.7
Coriobacteriales	order	31.3	100	95.7
Holdemanella	genus	31.4	66.7	32.8
Eubacteriales incertae sedis	norank	31.5	95.8	89.5
Bifidobacteriaceae	family	31.7	100	89.6
Fusobacteria	phylum	31.7	45.8	40.8
Fusobacteriia	class	31.8	45.8	40.7
Eggerthellales	order	31.8	100	97
Eggerthellaceae	family	31.9	100	97
Terrabacteria group	clade	31.9	100	99.9
Fusobacteriales	order	32	45.8	40.7
Collinsella	genus	32	91.7	89.4
Leuconostocaceae	family	32	62.5	54.4
Coriobacteriaceae	family	32.7	100	94.7
Bifidobacterium	genus	33	100	88.2
Pseudobutyrivibrio	genus	33.2	79.2	81.6
Turicibacter sanguinis	species	33.8	62.5	55.5
Bacteroides denticanum	species	34.2	70.8	21.9
Fusobacterium	genus	34.2	41.7	33.9
Erysipelotrichaceae	family	34.4	100	98.8
Dorea	genus	34.4	100	98.3
Natranaerobiales	order	34.5	54.2	21
Actinomycetaceae	family	34.6	87.5	82.5
Roseburia faecis	species	34.8	95.8	80.9
Veillonella montpellierensis	species	34.9	37.5	14.6
Holdemania	genus	65.7	95.8	77.6
Chlorobaculum	genus	67.4	50	20.2
Bacteroides ovatus	species	67.6	100	73.9
Anaerotruncus colihominis	species	69.1	100	65.8
Oscillospira	genus	75.1	75	55.5

What is striking is not higher counts, but certain bacteria are being seen a lot more often. In fact, no bacteria is seen less often with Long COVID people but the amount may be less. That is more types of bacteria but with lower levels than average.

Note: Percentile means the percentile ranking of samples for a specific bacteria. The expected percentile for a random sample of people is 50%ile. Thus a lower percentile means that the median of the group is less than the median of the population. A higher percentile means that the median of the group is higher than the median of the population. The severe skewness of bacteria distribution does not mean the the average of the sample is lower or higher than the average of the population — in fact, they may be the same. (Welcome to statistical gymnastics 301!!!)

The ME/CFS Connection

This type of novel analysis (using frequency of detection and not amount of bacteria) results in Long COVID and Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). being very similar at the microbiome level. see Bacteria Shifts Seen in Chronic Fatigue Syndrome.

Backstory

My son is born in 2009 and diagnosed with autism in 2011. When he was 3 months old he has lot of reflux and unable to digest milk always used to throw up and we ended up using antibiotics because of mucus forming issues and at 10 months he had few words.

• And at 18 months he got diagnosis’s of autism and was completely Non-Verbal.
• After removing gluten and dairy from his diet at age 3.5 he started saying words
• he also got diagnosed with Lyme and coinfections like bartonella and Babesia .
• Now he is 11 years still having lot of issues like his weight is just 55 Lbs  he has focus issues and lot/severe OCDs and tantrums and lot of rigidity and not conversational yet ,cognitive issues cannot understand abstract concepts and has lot of echolilia and  no social skills and gets head pain all of a sudden which might be PANS will last for few minutes and will be fine again.
• And he has lot of Gut issues like  failure to thrive even though his diet his healthy he does not gain weight at all and he has leaky gut and always have constipation issues  and poor digestion issues and picky eating and he complaints some times that his stomach hurts and some times his stomach gets very tight like gas forming. And he has brain and Gut inflammation.
• Very recently from couple of months  he started having Acid Reflux issues after eating he will be spitting for an hour as if something is coming back from his stomach. 
  • We also noticed that when ever he eats chicken and eggs he is more constipated. We did the GI work up and everything came up normal except one thing that he does not have enzymes to digest lactose and also we make sure he is not constipated and his bowls are moving everyday with some laxative.

We have two samples for this person, while we will use the last one for suggestions, a comparison may be spark insights.

Basic Analysis

Looking at the two samples, we see that things are very different than with the ME/CFS person in this post. Instead of over representation in rare bacteria, there is over representation in common bacteria (i.e. the bacteria that most people have).

	Earlier	Sample	Latest	Sample
Percentile	Genus	Species	Genus	Species
0 – 9	10	1	7	7
10 – 19	10	9	9	12
20 – 29	6	9	8	13
30 – 39	10	18	7	10
40 – 49	12	9	6	12
50 – 59	12	15	9	18
60 – 69	10	7	8	12
70 – 79	10	16	10	16
80 – 89	25	39	22	38
90 – 99	103	149	40	64
Std Dev	29.31	44.00	10.65	17.61

• Looking at “Potential Medical Conditions Detected” for both samples we see a very long list of candidate conditions for both samples
• For “Bacteria deemed Unhealthy”, again we have some long lists
• For “Dr. Jason Hawrelak Recommendations”, we have the earlier sample at 75%ile and the latest sample at 98.8%ile, i.e. “no issues”
• AI Computer Probiotics.
  • Earlier sample: L. Bulgaricus Probiotic Powder, miyarisan (jp) / miyarisan, PIANETA FARMA/KefiBios were top suggestions by with a low weight (1.0)
  • Later sample: Prescript-Assist®/SBO Probiotic as only suggest and with almost no weight (0.07)
• AI Computed supplements at 10% level: Neither sample had any.

There is the appearance of improvement between the sample. This may be solely due to the changes due to age (18 months between samples), or moving further away from microbiome disruptive events of the past.

Going Forward

We need to go with some caution because the child microbiome is different than an adult’s and most of the data we are using are from adults.

I am going to build the consensus in a slightly different way than usual:

•  Use JasonH (15 Criteria) – 6 bacteria picked
•  Standard Lab Ranges (+/- 2 Std Dev) – 17 bacteria picked
•  Box Plot Whisker – 59 bacteria picked
•  Kaltoft-Moltrup Normal Ranges – 92 bacteria picked
•  Percentile in top or bottom  10 % – 160 bacteria picked
• Canned Autism using U.S. Nation Library of Medicine Data – 8 bacteria picked
• Using Experimental Page using Official Diagnosis Autism only – 9 bacteria picked

Looking at Consensus Items

I scanned the top items and picked items that I suspect will be acceptable, easy to obtain and reasonable cost:

Take / Add to regime

• Herbs (may be added to food, tea or as capsules)
  • neem
  • syzygium aromaticum (clove)
  • thyme (thymol, thyme oil)
  • Ajwain (trachyspermum ammi)
  • ashwagandha (withania somnifera)
  • olea europaea (olive leaf)
• Probiotics (better choices are hard to obtain in the US at reasonable costs)
  • Lactobacillus salivarius
• Diet Style
  • Vegetarians
  • tea
  • rice
  • mastic gum (prebiotic)
  • saccharin
  • stevia
• Vitamins
  • vitamin b3 (niacin)
  • Cyanocobalamin (Vitamin B-12)
  • pyridoxine hydrochloride (vitamin B6)
  • retinoic acid,(Vitamin A derivative)
  • thiamine hydrochloride (vitamin B1)

There were some interesting AVOIDS (very different than ME/CFS people)

Avoid / Remove or Reduce use of

• magnesium (and foods rich in it, like walnuts)
• selenium
• zinc
• Conjugated Linoleic Acid (CLA)
• quercetin
• resveratrol (grape seed/polyphenols/red wine)
• oregano (origanum vulgare, oil) |
• noni
• Ginseng
• ginko
• inulin (prebiotic), jerusalem artichoke (prebiotic), chicory (prebiotic)
• Most probiotics!
• raffinose(sugar beet), lactulose

Seeing lactulose as a very strong to be avoid agrees so much with no tolerance for milk. I checked the antibiotics positive/negative benefit and was actually surprise to see on the positive impact many of the antibiotics used for ME/CFS and Lyme: fluoroquinolone (antibiotic)s, tetracycline (antibiotic)s, minocycline (antibiotic)s with the best one being vancomycin (antibiotic). This was interesting because “Vancomycin is used to treat colitis (inflammation of the intestine caused by certain bacteria) that may occur after antibiotic treatment.”[MedlinePlus]

Questions And Answers

1. Do you mean your current recommendations is not to use any probiotics or use only Lactobacillus salivarius strain of probiotics ?
   1. Only a very small number of probiotics appear to have a positive impact, less than 18. The other 39 came out with a negative effect. You need to read the labels carefully.
2. I also for the earlier sample you mentioned the PDF use of prescript assist soil based probiotic and also lactobacillus bulgaricus (probiotics) and lactobacillus kefiri . I have not used these so now do you think using them might be helpful based on the analysis 
   1. Those are on the recommended list, so YES
3. And based on your analysis what is most pathogenic bacteria that I need to address from the sample which is problematic such that I research and see how to reduce it?
   1. Unlike most people, this child has a huge amount of Lactobacillus bacteria, he has 98% more than anyone else in the database. Clicking on the link above (and those below) are the worst offenders where his levels are higher than 95% of peoples
   2. [Ruminococcus] gnavus, Actinomyces, Bacillus, Dorea, Erysipelatoclostridium ramosum, Shigella (especially Shigella dysenteriae),Streptococcus pyogenes, Streptococcus sanguinis
   3. In the video, I will show how you can find suggestions EXPLICIT for these.
4. What key strains of good bacteria do you think is missing for weight gain or in general ?
   1. Every good strain becomes bad if there are too many of them, for example Lactobacillus above. The microbiome should be viewed as “Yin/Yang” and not good and bad. I really do not have a clean answer for that question.
5. Which Lactobacillus strains does he have has 95% which I need to avoid further is it Lactobacillus Reutri and Lactobacillus Johnson and Lactobacillus planetarium are those the ones which I need to avoid completely to give or any other list?
   1. ALL Lactobacillus are similar with only small changes between them. They are a family. As with human families, they cross support each other. You want to lower all of the Lactobacillus, ideally have no lactobacillus probiotics.
6. Currently I started using sauerkraut , thinking he needs more Lactobacillus strains and I read sauerkraut has lot of different good strains. Would it be still okay to use it?
   1. He DOES NOT need more Lactobacillus strains — he needs a lot less!
   2. In my humble opinion NO. Two main reasons:
      1. You have no idea of which bacteria are in. Commercial versions usually do not list the
         species. On the few that do, it is very questionable if the label is correct.
         ” the species of lactic acid bacteria present in sauerkraut fermentations are more diverse than previously reported and include Leuconostoc citreum, Leuconostoc argentinum, Lactobacillus paraplantarum, Lactobacillus coryniformis, and Weissella sp.” [2007]
         For Weissella, he is at 90%ile — too high. He does not need more
7. Do I need to do anything to reduce Lactobacillus strains that are high?
   1. There is no studies that target explicit strains.
   2. melatonin supplement, B-vitamins reduce it too.
   3. A word of caution here. Are you going to target just one item of concern in several dozens by focusing on this item (with the potential cost of many other things becoming worst); or work from suggestions that are targeted to improve the microbiome as a whole?

In response to question #3, I did a hand picked of all of those over 95%ile on the Health Summary with the results shown below

A short list of Suggestions

To be discussed with family MD before starting

• Antibiotics
  • A course of vancomycin (antibiotic) to start
  • 3 weeks after this course is finished one of (piperacillin-tazobactam or gentamicin)
• Supplements (add one a week for 3 weeks than take 2 weeks off)
  • A baby aspirin once a day — watch especially for any improvement in brain activity
    • He may have a sub-clinical (mild) form of Antiphospholipid syndrome (thick blood) triggered by the microbiome shifts – I am reflecting my own experience here.
  • Vitamins B-3, B-6, B-12
  • N-Acetyl Cysteine (NAC),
• Diet
  • low carbohydrate diet with either (high-saturated fat diet/high beef diet or vegetarians)
    • Avoid magnesium rich foods
    • Use sunflower oil
    • rice
    • cruciferous vegetables (broccoli cabbage)
  • Ample use of the following herbs in cooking, as tea (or as capsules)
    • neem
    • syzygium aromaticum (clove)
    • Sumac(Rhus coriaria)
    • thyme (thymol, thyme oil)
    • Ajwain (trachyspermum ammi)
    • ashwagandha (withania somnifera)
• Probiotics
  • bacillus laterosporus (probiotic) would be the best choice — but finding that may be a challenge
  • REMEMBER he is very high in Lactobacillus and Bifidobacterium — what is in most probiotics…
• Fruit/ Juices
  • cherry
  • lemon
  • blackcurrant
  • strawberry
  • papaya
• Misc
  • melatonin supplement

Items to AVOID (You may wish to read the full list

• sesame cake/meal
• almonds/ almond skins, walnuts
• barley,oat whole grain,bran, wheat, quinoa
• pea (fiber, protein), bean
• fish oil
• apple
• pomegranate
• Kiwifruit
• Goji (berry,juice)
• dates
• corn
• plantain bananas
• Cacao

One of the easiest modern ways to do it, is to download this data as a CSV and save on your smart phone when shopping.

REMINDER: The items indicate odds/confidence in shifting the microbiome is the intended direction. It is NOT how effective it is. Each item in the take likely improves your odds of improving when taken; keep taking items the avoid list — continuing likely increase the odds of not changing.

Short bio: 35yr Male have had ME/CFS for about 7 years, see A review of a ME/CFS Microbiome for prior review plus backstory. This was my review for “A – Thryve:2021-11-21 self” below.

This person has had done three samples, so we will both look at the latest sample and across samples.

• A – Thryve:2021-11-21 self
• B – Thryve:2022-03-15 self (he used the microbiome prescription site himself to get next course adjustment)
• C – Thryve:2022-05-16 self (this review)

The key questions focus on objective improvement and subjective improvement.

General Health Issues

The evenness of Genus and Species across percentile is shown below

	A	A	B	B	C	C
Percentile	Genus	Species	Genus	Species	Genus	Species
0 – 9	11	16	6	9	11	15
19-Oct	12	30	15	30	19	27
20 – 29	19	31	20	24	12	31
30 – 39	18	35	23	45	16	33
40 – 49	16	24	20	37	18	30
50 – 59	21	31	25	45	21	33
60 – 69	18	20	17	30	14	22
70 – 79	16	23	11	28	16	23
80 – 89	5	14	16	24	13	21
90 – 99	3	14	13	20	5	14
Total	139	238	166	292	145	249
Std.Dev.	6.05	7.71	5.72	11.10	4.60	7.02

My reading is that at the Genus level, the microbiome is stablizing. An ideal microbiome would have a Standard Deviation of 0.0 (i.e. the appropriate percentage is in each class). We see for Genus move from 6.0 -> 5.7 -> 4.6. Species have a far greater degree of randomness because may species are not identified, most genus are identified.

Potential Medical Conditions Detected

The count has been similar: A:3 B:6 C:2 with the one items in common being Allergies.

Unhealth Bacteria

The counts were similar between all samples: A:18, B:20, C:21

Dr. Jason Hawrelak Recommendations

We had significant improvement between the first two samples and a slight loss going to the third: A: 56.5%(5) B:95.5% (8) C: 89% (7)

AI Computed Probiotics

AI Suggested Supplements

Using the default 10% level, we found samples A and B only suggested one supplement. C suggested 2 (L-Histidine and manganese). I looked up the item from A and B and saw that it had continued to improve. 🙂

Supplements	A	B	C
beta-alanine	7.3	9.2	17.3

Has there been positive change?

My reading of the above objective numbers is yes in several vectors. There was nothing show a clear negative change. Somethings stayed put — that is fine, it is small steps. As the picture below illustrates, it is not a direct line/tunnel through the mountain ranges of dysbiosis, we have to work our way across passes and valleys.

The “I don’t feel better” quicksand

I have too often seen — especially with people suffering from Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) — patients giving up on a course of action because they reached a point where they may state “I don’t feel better from doing this, so I am changing…”. For these people, this is often caused by several factors:

• They do not remember how they were actually 2 weeks or 2 months ago…
• Their MD have no objective tests to show progress
• They expect significant constant change constantly (they are frustrated waiting for improvement)

Using the microbiome and repeated testing, they can get objective measurement of changes instead of relying on subjective measurement being done under the influence of brain fog with memory problems.

In this person case, we do see objective improvement of the dysbiosis. What about subjective?

“You’re welcome to mention I have noticed improved sleep and lower anxiety despite my good and bad bacteria shifting around “

From the reader

Moving Forward

As reviewed above, we have no KEGG suggested probiotics, but do have these supplements suggested:

• L-Histidine – Percentile: 2.7
• manganese – Percentile: 3.7
• NADH – Percentile: 15.6 (this has been studied for ME/CFS
  • Effect of Dietary Coenzyme Q10 Plus NADH Supplementation on Fatigue Perception and Health-Related Quality of Life in Individuals with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Prospective, Randomized, Double-Blind, Placebo-Controlled Trial, 2021
  • Effect of coenzyme Q10 plus nicotinamide adenine dinucleotide supplementation on maximum heart rate after exercise testing in chronic fatigue syndrome – A randomized, controlled, double-blind trial 2015
  • Does oral coenzyme Q10 plus NADH supplementation improve fatigue and biochemical parameters in chronic fatigue syndrome? [2014]
  • Comparison of oral nicotinamide adenine dinucleotide (NADH) versus conventional therapy for chronic fatigue syndrome [2004]
  • Is NADH effective in the treatment of chronic fatigue syndrome? [2000]
  • [Nicotinamide adenine dinucleotide (NADH) in patients with chronic fatigue syndrome] [2010]
  • Therapeutic effects of oral NADH on the symptoms of patients with chronic fatigue syndrome [1999]
  • Chronic lactic acidosis in an adult. A new syndrome associated with an altered redox state of certain NAD-NADH coupled reactions [1970] – this paper was pre ME/CFS existing, but lactic acidosis has been establish as frequently happening with ME/CFS subsequently.

On a personal note, I used NADH during my 1999-2000 relapse (1st time diagnosis). I eventually switched to 400 mg of flushing niacin twice a day (after MD checked my liver function see facts) and have continue to do so (with liver being tested every year).

Getting suggestions based on US National Library of Medicine Studies

As is my pro forma approach, I did each of the following (with number of bacteria picked after):

•  Use JasonH (15 Criteria) – 8
•  Use Medivere (54 Criteria) – 8
•  Use Metagenomics (59 Criteria) – 8
•  Use Nirvana/CosmosId (36 Criteria) – 8
•  Use XenoGene (22 Criteria) – 8
•  Standard Lab Ranges (+/- 2 Std Dev) – 2 (Too High:   Bacteroides clarus, Roseburia hominis)
•  Box Plot Whisker – 39
•  Kaltoft-Moltrup Normal Ranges – 85
•  Percentile in top or bottom 10% 69

The new layout of the consensus page is shown below

My suggestion for 3 probiotics to rotate thru are:

• bifidobacterium animalis lactis (probiotics) – the cheapest source (per BCFU) is Custom Probiotics
• Akkermansia muciniphila (probiotic) – the only source is Pendulum
• Any bacillus only probiotic containing bacillus coagulans (probiotics) and Bacillus clausii (Probiotics)
  • Many possible products, search this page

For more information on probiotics see the bottom section of this recent review.

For supplements, there are only 3 easily accessed items that are positive, everything else is negative impact!!: Ferric citrate (iron supplement), magnesium (commonly used for ME/CFS) and vitamin k2

For other things, see the video or the suggestions on your microbiome.

Bottom Line

You are making objective progress. A word of caution, if some of the items that you are currently taking on the avoid list, slowly remove them by reducing amount and watching for potential adverse effect. Some of the positive objective changes may be due to them (there is a risk of a feedback loop: if you are taking them, they are not needed BUT it you stop taking them, your microbiome may devolve to a state needing them).

Last – Using Symptoms

This is EXPERIMENTAL. It is a thought experiment and I am still learning it’s behavior. For some symptoms it may reduce awesome results, for others it may improve one set of symptoms at a cost of other symptoms getting worst. I picked two of the more unusual symptoms that he had:

• Comorbid: Methylation issues (MTHFR)
• Immune: Chronic Sinusitis

This resulted in this list being selected with a very strong Filter (first time I have seen this)

Rank	Name	Your value	Percentile
class	Flavobacteriia	21	7
order	Chromatiales	21	9.4
order	Flavobacteriales	21	7
order	Marinilabiliales	21	13.5
phylum	Tenericutes	42	9.5
species	Bifidobacterium bohemicum	21	11.8
species	Eubacterium ramulus	8720	95.5
species	Prevotella disiens	946	84.1

With the top suggestions for this small subset being:

Modifier	Confidence
daesiho-tang	0.982
chicory (prebiotic)	0.955
inulin (prebiotic)	0.955
jerusalem artichoke (prebiotic)	0.955  📏
resveratrol (grape seed/polyphenols/red wine)	0.955  📏
glycyrrhizic acid (licorice)	0.509  📏

I would suggest using it to increase the priority of some items that are positive suggestions in the consensus list, I would not go with using this set of suggestions alone.

Questions from Reader

• Ferric Citrate ,  haven’t been able to find this type? Have you seen it anywhere? Also how would one figure out the dose for gut bacteria shifting?
  • I am an ex-science teacher and thus know it more common name, Iron Citrate. Swanson and others sells it.
• Bacillus- taking terraflora , think I’m up to 6 caps. I saw in a study I need to get to 20 !! …I also have prescript on hand BUT that has a lot of other SBO strains. Would you stuck to TERRAflora for now?  
  • I would keep the Prescript Assist on the shelf, and keep to Terraflora, I would keep increasing the dosage every second day until the bottle was finished. I would look around for ones with similar probiotics for the next cycle, for example Youtheory, Spore Probiotic, 6 Billion CFU, 60 Vegetarian Capsules – for two reasons:
    • Cheaper per BCFU (and also higher BCFU per dosage)
    • Different strains often helps because they produce slightly different products
• Miyarisan , I thought I saw this in my results somewhere , maybe it was far down the list…would you save or finish if you had my results?
  • It is on the list, I would finish it before starting the next cycle of probiotics (REMEMBER: we want to be rotating the probiotics – not take them continuously)
    

• Akkermansia – I have 2 bottle of this stuff actually from pendulum . I read you and your wife has taken it. How much did you take or I know it’s a new product but if you’ve seen a study with dosing please let me know. 
  • The one existing study used 10 BCFU/day, and the bottle reads 0.4 gm. Lacking more information, I would just keep to the bottle recommended dosage.
• NADH- I have the flush stuff and cq10? Do you think that combo works or does it have to be Nadh?
  • Personally, I found flush niacin had greater impact and still look forward to my morning flush to get the mind working (it improves oxygen delivery because it’s a vascular dilator). Assuming you can tolerate the flush.

ALWAYS REVIEW WITH YOUR MEDICAL PROFESSIONAL FIRST