Bacteria Shifts Seen in Chronic Fatigue Syndrome

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_nameTax_rankSample Frequency
of Detection
Population Frequency
of Detection
Shift
Phocaeicola plebeiusspecies125.2Lower
Oscillatorialesorder13.55.1Lower
Bacteroides gallinarumspecies13.54.5Lower
Aerococcaceaefamily14.14.5Lower
Phocaeicola coprocolaspecies15.15.4Lower
Desulfovibriogenus22.98.8Lower
Collinsellagenus258.7Lower
Hathewayagenus30.210.6Higher
Bacteroides ovatusspecies30.210.6Higher
Anaerotruncus colihominisspecies30.210.4Higher
Bacteroides rodentiumspecies30.210.6Higher
Sample Size: 58

OmbreLabs / Thryve

Tax_nameTax_rankSample Frequency
of Detection
Population Frequency
of Detection
Shift
Alteromonadaceaefamily9.43.4Lower
Paenibacillusgenus126.6Lower
Phocaeicola plebeiusspecies127.1Lower
Bacteroides gallinarumspecies13.57.3Lower
Oscillatorialesorder13.54.8Lower
Planococcaceaefamily13.56.7Lower
Aerococcaceaefamily14.16.8Lower
Phocaeicola coprocolaspecies15.17.5Lower
Turicibacter sanguinisspecies15.15.1Lower
Sarcinagenus19.30.4Lower
[Ruminococcus] torquesspecies19.88.1Lower
Desulfovibriogenus22.97.2Lower
Ruminiclostridiumgenus22.98.2Lower
Peptostreptococcaceaefamily248.2Lower
Collinsellagenus257.2Lower
Anaerostipesgenus26.68.3Lower
Eubacteriumgenus29.28.3Lower
Eubacteriales incertae sedisnorank29.78Lower
Clostridiumgenus30.28.2Higher
Sphingobacterialesorder30.24.8Higher
Blautia hanseniispecies30.25.3Higher
Oscillospiragenus30.20Higher
Bacteroides ovatusspecies30.27.2Higher
Anaerotruncus colihominisspecies30.26.7Higher
Blautia wexleraespecies30.28.3Lower
Bacteroides rodentiumspecies30.27.4Higher
Sphingobacteriiaclass30.24.8Higher
Sphingobacteriaceaefamily30.24.8Higher
Hathewayagenus30.24.1Higher
Anaerofilumgenus30.24.2Higher
Actinobacteriaphylum30.28.3Lower
Sample Size 51

uBiome

Tax_nameTax_rankSample Frequency
of Detection
Population Frequency
of Detection
Shift
Planococcaceaefamily13.50.3Lower
Bacteroides gallinarumspecies13.50.1Lower
Oscillatorialesorder13.50.1Lower
Aerococcaceaefamily14.10.6Lower
Phocaeicola coprocolaspecies15.10.4Lower
Turicibacter sanguinisspecies15.13.3Lower
Sarcinagenus19.35.4Lower
Ruminiclostridiumgenus22.90.2Higher
Adlercreutzia equolifaciensspecies22.93.8Lower
Desulfovibriogenus22.92.7Lower
Peptostreptococcaceaefamily245.6Lower
Collinsellagenus255.5Lower
Anaerostipesgenus26.65.6Lower
Eubacteriumgenus29.21.1Higher
Eubacteriales incertae sedisnorank29.75.5Lower
Oscillospiragenus30.24.2Higher
Anaerotruncus colihominisspecies30.22.1Higher
Blautia wexleraespecies30.25.4Lower
Bacteroides rodentiumspecies30.20.1Higher
Sphingobacteriiaclass30.20.1Higher
Sphingobacteriaceaefamily30.20Higher
Anaerofilumgenus30.21.8Higher
Actinobacteriaphylum30.25.6Lower
Bacteroides ovatusspecies30.22.9Higher
Clostridiumgenus30.25.5Higher
Sphingobacterialesorder30.20.1Higher
Blautia hanseniispecies30.21.8Higher

Common across all labs

Amount of Bacteria

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

Tax_nameTax_rankOmbreBiomesightuBiome
PaenibacillusgenusLowerHigherHigher
Phocaeicola plebeiusspeciesLowerHigherHigher
OscillatorialesorderLowerHigherHigher
PlanococcaceaefamilyLowerHigherHigher
Phocaeicola coprocolaspeciesLowerHigherHigher
Turicibacter sanguinisspeciesLowerHigherHigher
SarcinagenusLowerHigherHigher
Bacteroides gallinarumspeciesLowerLowerHigher
The shift in bacteria count observed

Frequency of Detection

Here we have agreement across all of the labs

Tax_nameTax_rankOmbreBiomesightuBiome
PaenibacillusgenusMoreMoreMore
Phocaeicola plebeiusspeciesMoreMoreMore
Bacteroides gallinarumspeciesMoreMoreMore
OscillatorialesorderMoreMoreMore
PlanococcaceaefamilyMoreMoreMore
Phocaeicola coprocolaspeciesMoreMoreMore
Turicibacter sanguinisspeciesMoreMoreMore
SarcinagenusMoreMoreMore
AerococcaceaefamilyMoreMore
DesulfovibriogenusMoreMore
RuminiclostridiumgenusMoreMore
PeptostreptococcaceaefamilyMoreMore
CollinsellagenusMoreMore
AnaerostipesgenusMoreMore
EubacteriumgenusMoreMore
Eubacteriales incertae sedisnorankMoreMore
ClostridiumgenusMoreMore
SphingobacterialesorderMoreMore
Blautia hanseniispeciesMoreMore
OscillospiragenusMoreMore
Bacteroides ovatusspeciesMoreMore
Blautia wexleraespeciesMoreMore
SphingobacteriiaclassMoreMore

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 COVIDOmbre
ME/CFS
Biomesight
ME/CFS
Ubiome
ME/CFS
MicrococcaceaeMoreMoreMore
PeptostreptococcaceaeMoreMoreMore
Butyricimonas virosaMoreMoreMore
SarcinaMoreMoreMore
EnterobacterMoreMoreMore
LactobacillaceaeMoreMoreMore
CoriobacteriiaMoreMoreMore
Slackia faecicanisMoreMore
RhodovibrionaceaeMoreMore
Blautia wexleraeMoreMore
Salinicoccus luteusMoreMore
StaphylococcaceaeMoreMore
BifidobacterialesMoreMore
Holdemanella biformisMoreMore
CoriobacterialesMoreMore
HoldemanellaMoreMore
Eubacteriales incertae sedisMoreMore
FusobacteriiaMoreMore

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

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