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.