Metabolic adaptation and fragility in healthy 3-D in vitro skeletal muscle tissues exposed to [CFS] and Long COVID-19 sera, 2025, Mughal+

[DMissa]

There is a lot of talk in this thread about muscle culture and seahorse etc, I haven't gotten to read the paper yet but useful things to look into would be a) whether activity matched controls b) passaging/handling of the cultures (primary muscle cell phenotypes change with doublings - is that what has been used? havent looked in detail at what was cultured) c) absolute basal oxygen consumption rate values not being negative or close to 0 - if reported as normalised to cell number or stained DNA fluorescence or total protein this might be harder to glean d) not a huge amount of variability after ionophore injection (if used, ia assume so) this can cause cells to swell up and detach which confounds measurements, many aspects of the protocol have to be optimised to avoid it such as instrument mixing protocol, choice or presence of adherence matrix, incubation times, etc

sorry to offload homework, under the pump

my interactions with the lead author leave me confident that pitfalls would have been avoided but yes those are the first things that spring to mind when it comes to evaluating this kind of work. there are others but too technical to explain briefly

 

[DMissa]

I also wonder how this relates to the study by @chillier which found no difference in oxygen consumption rate when ME/CFS serum was added to myoblasts. Do these studies contradict each other?

is it the same same cell type and what are the differences in how they were handled would be my questions (have absolutely no time to look)

 

[jnmaciuch]

We have a student in the lab doing this, I sat down with her and went through it a few days ago, actually. It was pretty objective and automated. That mito morphology package was part of the workflow, i just dont remember the full suite she was using. So it's possible this work here is also objective and automated

Good to know!

 

[hotblack]

I’m only just digging into this in more detail and others have I think raised most of the questions that popped into my head already. But a couple of other thoughts

Could the difference be that this is investigating a muscle tissue preparation (with a longer setup time) which could then include secreted extracellular matrix components, vs multiple but independent and disorganised muscle cells in a well? Abnormal signalling and pathological cell effects might require ECM components.

Interesting. I wondered what differences there could be between the myoblast culture and this sort of grown muscle model, I know nothing about this area but it would be interesting to understand more and of the differences could tell us something interesting about the mechanism.

What I can’t figure out is what would make this study resemble the Fluge et al. results when the Ryback study tried to mimic the Fluge study’s protocol as much as possible. The best idea I have so far is that this study and the Fluge study included participants in active PEM, but no way to really assess that.

Would this effect or serum factor only being present in active PEM tell us anything? I also wonder how this fits into the narrative in this paper of the whole process being modelled (they seem to imply they are triggering PEM by putting strain on the muscle).

Sample size has been mentioned, presumably the small sample sizes in both Fluge and this paper mean they may have picked up something which is only present in a subset of ME/CFS patients but not all?

I don’t think we have any attempts to correlate with symptoms severity or other patient characteristics here, probably impossible with the small sample sizes but could be interesting and is something Ryback et al were able to do.

What would the differences in concentration mean and why so different between the papers? Is there a ‘standard’ concentration used for these sort of experiments or one which most closely matches real world conditions?

As with a number of these papers I come back to the idea that it may have found something but it’s not clear what that is. The narrative weaved distracts and my lack of knowledge of the area doesn’t help glean what the data is telling us. Seems interesting though!

 

[wigglethemouse]

The Seahorse testing only used a small number of patients. Talking to researchers who've measured PBMC's, and the Rybeck myoblast paper showed, individual results are either high, low, or average. If you use a low number of patients the mean could be anywhere.

So I don't think we should read too much into that part of the paper right now.

 

[wigglethemouse]

I remember Jeroen den Dunnen speaking about culturing muscles cells and creating "PEM in a dish" in Berlin. Since he is slowly also focusing on muscle cells, this is where they'll try to replicate these findings as well? I should ask.

Thanks for posting the video again. This was really good. That team is creative, smart, adaptable, and able to get things done. I liked how he had complete answers to questions, none of this "I'll need to get back to you". And he collaborates and recognises others work. I really enjoyed the talk.

 

[Dude]

Cort’s take on the study:

"Something in the Blood" Again! ME/CFS and Long COVID Serum Locks the Muscles Down - Health Rising

Geoff’s Narration The GIST Muscles on a Chip Whoa, another muscle study. We recently reported on a proteomic study suggesting that muscle repair problems contribute to post-exertional malaise in ME/CFS. Now, we have a direct muscle test – and even better – we get to see whether something in the […]

www.healthrising.org

 

[V.R.T.]

Cort’s take on the study:

"Something in the Blood" Again! ME/CFS and Long COVID Serum Locks the Muscles Down - Health Rising

Geoff’s Narration The GIST Muscles on a Chip Whoa, another muscle study. We recently reported on a proteomic study suggesting that muscle repair problems contribute to post-exertional malaise in ME/CFS. Now, we have a direct muscle test – and even better – we get to see whether something in the […]

www.healthrising.org

I'm not a huge fan of Cort's 'everything is true even conflicting things' approach to MECFS science but the below quote sounds quite a good idea to me:

What we need is a serious effort to break the logjam: a multi-center, blinded, consortium-based serum/plasma “challenge” study that handles the samples in the same way, uses standardized assays, determines if a dose-response pattern is present, identifies a specific component that’s causing trouble, and then removes it to see if the same response occurs. Surely we have enough evidence to support a major study like that.

This study would test a variety of tissues (platelets, endothelial NO, BBB endothelial activation, cardiomyocytes, 3D muscle) against a range of agents (IgG, EVs/exosomes, complement, etc.). Once it was clear which component affected which tissue, researchers would attempt to identify the active agent; i.e., which antibodies, EVs, proteins, or small molecules were causing the problem. Then the suspect factor would be introduced and removed multiple times to assess the robustness of the finding.

If we did that, we would know if something in the blood is contributing to ME/CFS or long COVID, and if it was, we would have a treatment target, and the opportunity to directly affect patients.

 

[Utsikt]

I'm not a huge fan of Cort's 'everything is true even conflicting things' approach to MECFS science but the below quote sounds quite a good idea to me:

Aren’t there thousands of components in the blood, and umpteen different assays to test?

How do you pick the relevant ones? Sounds like a pipe dream, but someone with much more knowledge than me might be able to chime in?

 

[forestglip]

Aren’t there thousands of components in the blood, and umpteen different assays to test?

How do you pick the relevant ones? Sounds like a pipe dream, but someone with much more knowledge than me might be able to chime in?

I don't know much either, but I thought there was a way to filter molecules by size. So you'd split patient serum into large molecules and small molecules, and see which of these still has an effect on the muscle like in this study. Then split the one that does by size again and try again. It might at least narrow it down a bit.

 

[Atlas]

So you'd split patient serum into large molecules and small molecules, and see which of these still has an effect on the muscle like in this study. Then split the one that does by size again and try again.

In software development a similar concept is called a binary search — you split the search field in two, then see if what you're looking for is on the left or right side according to a test (requires the items to be sortable by a value, in this case mass). Then repeat that recursively until you find the item you're looking for.


In a video a year or so ago Ron Davis mentioned a potential plan to do this (I think with some kind of advanced mass spectrometry?) to find the "something in the blood". I forget what technical name he called it, ("bisecting"?), but yes that's (simplified) how they planned to look for the unknown factor.


(Of course, if the unknown factor(s) is larger than a single molecule I'm not sure if this kind of separation by mass would be possible? But it may still offer clues, and some kind of search by elimination could still offer clues.)